Project Part 2

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This notebook contains the code samples found in Chapter 3, Section 5 of Deep Learning with R. Note that the original text features far more content, in particular further explanations and figures: in this notebook, you will only find source code and related comments.

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Data Exploration & Preparation

• Our goal in the second part of the assignment is to predict how good a (new) customer will pay back their credit card depts. In the data set application data from current customers (the first 18 attributes) together with their status (last attribute; target) are given.
  
• The attributes from the applications are

Attribute Name	Explanation	Remarks
ID	Client	number
CODE_GENDER	Gender
FLAG_OWN_CAR	Is there a car
FLAG_OWN_REALTY	Is there a property
CNT_CHILDREN	Number of children
AMT_INCOME_TOTAL	Annual income
NAME_INCOME_TYPE	Income category
NAME_EDUCATION_TYPE	Education level
NAME_FAMILY_STATUS	Marital status
NAME_HOUSING_TYPE	Way of living
DAYS_BIRTH	Birthday	Count backwards from current day (0), -1 means yesterday
DAYS_EMPLOYED	Start date of employment	Count backwards from current day(0). If positive, it means the person unemployed.
FLAG_MOBIL	Is there a mobile phone
FLAG_WORK_PHONE	Is there a work phone
FLAG_PHONE	Is there a phone
FLAG_EMAIL	Is there an email
OCCUPATION_TYPE	Occupation
CNT_FAM_MEMBERS	Family size

• The last attribute status contains the “pay-back behavior”, i.e. when did that customer pay back their depts:
  • 0: 1-29 days past due
  • 1: 30-59 days past due
  • 2: 60-89 days overdue
  • 3: 90-119 days overdue
  • 4: 120-149 days overdue
  • 5: Overdue or bad debts, write-offs for more than 150 days
  • C: paid off that month
  • X: No loan for the month Please note: We are learning only the pay-back behavior. The decision, i.e. if we accept a customer or not, is done in another process step – not here!

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Main task

• Design your network. Why did you use a feed-forward network, or a convolutional or recursive network – and why not?
  
• Use k-fold validation (with k = 10) to find the best hyperparameters for your network.
• Use the average of the accuracy to evaluate the performance of your trained network.
• Find a “reasonable” good model. Argue why that model is reasonable. If you are not able to find a reasonable good model, explain what you all did to find a good model and argue why you think that’s not a good model.
  
• Save your trained neural network with save_model_hdf5. Also save your data sets you used for training, testing and validation.

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Some hints

• Data preprocessing is easier here; no feature engineering is needed.
• You may be able to reuse parts of the exercises we used in our examples during lectures.
• All in- and output values need to be floating numbers (or integers in exceptions) in the range of [0,1].
• Please note that a neural network expects a R matrix or vector, not data frames. Transform your data (e.g. a data frame) into a matrix with data.matrix if needed.
  
• There are some models which show an accuracy higher than 90% (!) for training (and test) data – after learning more than 1000 epochs.

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Important notes

• Single-label, Multiclass classification problem on page 73 in Deep Learning with R
• Spaces must be removed in between ‘{r}' and '’, else an error with ‘’ will be produced
• K-Fold Validation on page 83ff and 94ff in Deep Learning with R
• Page 110, use Last-Layer activation softmax and loss function categorical_crossentropy
• Convolutional network ausgeschlossen, weil hauptsächlich Pattern recognition/image classification
• Recursive ausgeschlossen, weil hauptsächlich für TimeSeries-Vorhersagen verwendet, oder für Vorhersagen
• Feed-Forward, weil Classification-Task

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Data import

#install.packages("tidymodels")
#install.packages("themis")
library(here)
library(tidyverse)
library(ggplot2)
library(dplyr)
library(tensorflow)
library(tfdatasets)
library(tidymodels)
library(keras)
library(caret)
library(themis)
#LOAD DATA
setwd(getwd())
dataIn = "../Data/Dataset-part-2.csv"
data_in <- read.csv(dataIn,header = TRUE, sep =',')
#View(data_in)
data <- data.frame(data_in)
summary(data)

       ID          CODE_GENDER        FLAG_OWN_CAR       FLAG_OWN_REALTY     CNT_CHILDREN     AMT_INCOME_TOTAL 
 Min.   :5008804   Length:67614       Length:67614       Length:67614       Min.   : 0.0000   Min.   :  26100  
 1st Qu.:5465941   Class :character   Class :character   Class :character   1st Qu.: 0.0000   1st Qu.: 112500  
 Median :5954270   Mode  :character   Mode  :character   Mode  :character   Median : 0.0000   Median : 157500  
 Mean   :5908133                                                            Mean   : 0.4206   Mean   : 178867  
 3rd Qu.:6289080                                                            3rd Qu.: 1.0000   3rd Qu.: 225000  
 Max.   :7965248                                                            Max.   :19.0000   Max.   :6750000  
 NAME_INCOME_TYPE   NAME_EDUCATION_TYPE NAME_FAMILY_STATUS NAME_HOUSING_TYPE    DAYS_BIRTH     DAYS_EMPLOYED   
 Length:67614       Length:67614        Length:67614       Length:67614       Min.   :-25201   Min.   :-17531  
 Class :character   Class :character    Class :character   Class :character   1st Qu.:-19438   1st Qu.: -2886  
 Mode  :character   Mode  :character    Mode  :character   Mode  :character   Median :-15592   Median : -1305  
                                                                              Mean   :-15914   Mean   : 62022  
                                                                              3rd Qu.:-12347   3rd Qu.:  -321  
                                                                              Max.   : -7489   Max.   :365243  
   FLAG_MOBIL FLAG_WORK_PHONE    FLAG_PHONE       FLAG_EMAIL     OCCUPATION_TYPE    CNT_FAM_MEMBERS 
 Min.   :1    Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   Length:67614       Min.   : 1.000  
 1st Qu.:1    1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000   Class :character   1st Qu.: 2.000  
 Median :1    Median :0.0000   Median :0.0000   Median :0.0000   Mode  :character   Median : 2.000  
 Mean   :1    Mean   :0.2028   Mean   :0.2742   Mean   :0.1005                      Mean   : 2.174  
 3rd Qu.:1    3rd Qu.:0.0000   3rd Qu.:1.0000   3rd Qu.:0.0000                      3rd Qu.: 3.000  
 Max.   :1    Max.   :1.0000   Max.   :1.0000   Max.   :1.0000                      Max.   :20.000  
    status         
 Length:67614      
 Class :character  
 Mode  :character  
                   
                   
                   

plot(data$status)

##Cleanup

# Check for duplicates 
sum(duplicated(data))

[1] 0

# No duplicates

#Remove ID (irrelevant) and FLAG_MOBIL (always 1)
data <- data %>% select(-ID, -FLAG_MOBIL)
cols <- c("CODE_GENDER","FLAG_OWN_CAR","FLAG_OWN_REALTY","NAME_INCOME_TYPE","NAME_EDUCATION_TYPE", "NAME_FAMILY_STATUS", "NAME_HOUSING_TYPE","FLAG_WORK_PHONE","FLAG_PHONE","FLAG_EMAIL", "OCCUPATION_TYPE","status")
cols

 [1] "CODE_GENDER"         "FLAG_OWN_CAR"        "FLAG_OWN_REALTY"     "NAME_INCOME_TYPE"   
 [5] "NAME_EDUCATION_TYPE" "NAME_FAMILY_STATUS"  "NAME_HOUSING_TYPE"   "FLAG_WORK_PHONE"    
 [9] "FLAG_PHONE"          "FLAG_EMAIL"          "OCCUPATION_TYPE"     "status"             

data[cols] <- lapply(data[cols],factor)

# Replacing empty values with "Unknown"
levels(data$OCCUPATION_TYPE) <- c(levels(data$OCCUPATION_TYPE), "Unknown")
data$OCCUPATION_TYPE[is.na(data$OCCUPATION_TYPE)] <- "Unknown"

# Replacing C and X in Status
levels(data$status)[levels(data$status)=="C"] <- "6"
#data$status[data$status == "X"] <- 7
levels(data$status)[levels(data$status)=="X"] <- "7"
# #Convert factors into numericals
# data %<>% mutate_if(is.factor, as.numeric)

summary(data)

 CODE_GENDER FLAG_OWN_CAR FLAG_OWN_REALTY  CNT_CHILDREN     AMT_INCOME_TOTAL              NAME_INCOME_TYPE
 F:43924     N:43107      N:21090         Min.   : 0.0000   Min.   :  26100   Commercial associate:15640  
 M:23690     Y:24507      Y:46524         1st Qu.: 0.0000   1st Qu.: 112500   Pensioner           :11982  
                                          Median : 0.0000   Median : 157500   State servant       : 5044  
                                          Mean   : 0.4206   Mean   : 178867   Student             :    4  
                                          3rd Qu.: 1.0000   3rd Qu.: 225000   Working             :34944  
                                          Max.   :19.0000   Max.   :6750000                               
                                                                                                          
                    NAME_EDUCATION_TYPE            NAME_FAMILY_STATUS           NAME_HOUSING_TYPE
 Academic degree              :   38    Civil marriage      : 6016    Co-op apartment    :  227  
 Higher education             :16890    Married             :44906    House / apartment  :60307  
 Incomplete higher            : 2306    Separated           : 4125    Municipal apartment: 2303  
 Lower secondary              :  716    Single / not married: 9528    Office apartment   :  587  
 Secondary / secondary special:47664    Widow               : 3039    Rented apartment   : 1020  
                                                                      With parents       : 3170  
                                                                                                 
   DAYS_BIRTH     DAYS_EMPLOYED    FLAG_WORK_PHONE FLAG_PHONE FLAG_EMAIL    OCCUPATION_TYPE  CNT_FAM_MEMBERS 
 Min.   :-25201   Min.   :-17531   0:53904         0:49071    0:60819    Unknown    :20699   Min.   : 1.000  
 1st Qu.:-19438   1st Qu.: -2886   1:13710         1:18543    1: 6795    Laborers   :12425   1st Qu.: 2.000  
 Median :-15592   Median : -1305                                         Sales staff: 6899   Median : 2.000  
 Mean   :-15914   Mean   : 62022                                         Core staff : 6059   Mean   : 2.174  
 3rd Qu.:-12347   3rd Qu.:  -321                                         Managers   : 4950   3rd Qu.: 3.000  
 Max.   : -7489   Max.   :365243                                         Drivers    : 4427   Max.   :20.000  
                                                                         (Other)    :12155                   
     status     
 0      :52133  
 1      : 6491  
 7      : 5790  
 6      : 1805  
 2      :  712  
 5      :  374  
 (Other):  309  

Preprocessing

set.seed(1)
trainIndex <- initial_split(data, prop = 0.8, strata = status) 
trainingSet <- training(trainIndex)
testSet <- testing(trainIndex)
status_folds <- vfold_cv(trainingSet, v = 10, strata = status)
status_folds

#  10-fold cross-validation using stratification 

# Remove outliers (Out of 1.5x Interquartile Range) only on training set
# CNT_CHILDREN
boxplot(trainingSet$CNT_CHILDREN, horizontal=TRUE, main="CNT_CHILDREN")

Q1_Child <- quantile(trainingSet$CNT_CHILDREN, .25)
Q3_Child <- quantile(trainingSet$CNT_CHILDREN, .75)
IQR_Child <- IQR(trainingSet$CNT_CHILDREN)
# Now we keep the values within 1.5*IQR of Q1 and Q3
trainingSet <- subset(trainingSet, trainingSet$CNT_CHILDREN > (Q1_Child - 1.5*IQR_Child) & trainingSet$CNT_CHILDREN < (Q3_Child + 1.5*IQR_Child))
dim(trainingSet)

[1] 53330    17

# AMT_INCOME_TOTAL
boxplot(trainingSet$AMT_INCOME_TOTAL, horizontal=TRUE, main="AMT_INCOME_TOTAL")

Q1_AIT <- quantile(trainingSet$AMT_INCOME_TOTAL, .25)
Q3_AIT <- quantile(trainingSet$AMT_INCOME_TOTAL, .75)
IQR_AIT <- IQR(trainingSet$AMT_INCOME_TOTAL)
# Now we keep the values within 1.5*IQR of Q1 and Q3
trainingSet <- subset(trainingSet, trainingSet$AMT_INCOME_TOTAL > (Q1_AIT - 1.5*IQR_AIT) & trainingSet$AMT_INCOME_TOTAL < (Q3_AIT + 1.5*IQR_AIT))
dim(trainingSet)

[1] 51748    17

set.seed(5)
preprocRecipe <-
  recipe(status ~., data = data) %>%
  step_dummy(all_nominal(), -status,  one_hot = TRUE) %>%
  step_range(all_predictors(), -all_nominal(), min = 0, max = 1)%>%
 # step_downsample(status, over_ratio = 1) %>%
 # step_smote(status, over_ratio = 1, skip=TRUE) %>%
 # step_smotenc(status, over_ratio = 1) %>%
 #step_adasyn(status, over_ratio = 1) %>%
 #step_nearmiss(status, over_ratio = 1) %>%
   
  step_dummy(status,  one_hot = TRUE)# %>%

In this step the above defined receipt is extracted using the prep() function, and then use the bake() function to transform a set of data based on that recipe.

# retain = TRUE and new_data = NULL ensures that pre-processed trainingSet is returned 
trainingSet_processed <- preprocRecipe %>%
  prep(trainingSet, retain = TRUE) %>%
  bake(new_data = NULL)
testSet_processed <- preprocRecipe %>%
  prep(testSet) %>%
  bake(new_data =testSet)

#summary(trainingSet_processed)

Check data

# summarize the class distribution
percentage <- 100-prop.table(table(data$status)) * 100
cbind(freq=table(data$status), percentage=percentage)

   freq percentage
0 52133   22.89615
1  6491   90.39992
2   712   98.94696
3   195   99.71160
4   114   99.83140
5   374   99.44686
6  1805   97.33043
7  5790   91.43668

class_weights <- list("0"=1,"1"=100)

# Turn data frame into data matrix
matrix_data <- trainingSet_processed %>% select(-tail(names(trainingSet_processed), 8))
matrix_targets <- trainingSet_processed %>% select(tail(names(trainingSet_processed), 8))

matrix_data_test  <- testSet_processed %>% select(-tail(names(testSet_processed), 8))
matrix_targets_test  <- testSet_processed %>% select(tail(names(testSet_processed), 8))

#Subset only 100 entries for testing
#matrix_data <- matrix_data[1:100, ]
#matrix_targets <- matrix_targets[1:100, ]

Build Model

#train_data <- matrix_data
train_data <- data.matrix(matrix_data)
test_data <- data.matrix(matrix_data_test)
train_targets <- data.matrix(matrix_targets)
test_targets <- data.matrix(matrix_targets_test)

# Function to build the model
build_model <- function() {
  model <- keras_model_sequential() %>%
    #layer_batch_normalization(axis = -1L, input_shape = dim(train_data)[[2]]) %>%
    layer_dense(units = 64, activation = "relu", input_shape = dim(train_data)[[2]]) %>%
    layer_dense(units = 64, activation = "relu") %>%
    #layer_dropout(0.3) %>%
    layer_dense(units = 64, activation = "relu") %>%
    layer_dense(units = 64, activation = "relu") %>%
    layer_dense(units = 64, activation = "relu") %>%
    layer_dense(units = 8, activation = "softmax") 

  model %>% compile(
    optimizer = optimizer_sgd(learning_rate = 0.2),
    loss = "categorical_crossentropy",
    metrics = "categorical_accuracy"
  )

}

K-Fold-Validation

k <- 2
indices <- sample(1:nrow(train_data))
folds <- cut(indices, breaks = k, labels = FALSE)

num_epochs <- 1500
all_acc_histories <- NULL
for (i in 1:k) {
  cat("processing fold #", i, "\n")

  val_indices <- which(folds == i, arr.ind = TRUE)
  val_data <- train_data[val_indices,] #test_data#
  val_targets <- train_targets[val_indices,] #test_targets#
  
  partial_train_data <- train_data[-val_indices,]
  partial_train_targets <- train_targets[-val_indices,]
  model <- build_model()

  # Train the model (in silent mode, verbose=0)
  # Batch size https://stats.stackexchange.com/questions/153531/what-is-batch-size-in-neural-network
  # One epoch = one forward pass and one backward pass of all the training examples
  # Batch size = the number of training examples in one forward/backward pass. The higher the batch size, the more memory space you'll need.
  # Number of iterations = number of passes, each pass using [batch size] number of examples. To be clear, one pass = one forward pass + one backward pass (we do not count the forward pass and backward pass as two different passes).
  # Batch size 32 much faster than 1, also the smaller the batch the less accurate the estimate of the gradient will be.
  history <- model %>% fit(
    partial_train_data, partial_train_targets,
    validation_data = list(val_data, val_targets),
    epochs = num_epochs, batch_size = 512, verbose = 2, class_weights = percentage
  )
  acc_history <- history$metrics$val_categorical_accuracy
  all_acc_histories <- rbind(all_acc_histories, acc_history)
}

processing fold # 1 
Epoch 1/1500
51/51 - 1s - loss: 0.8994 - categorical_accuracy: 0.7598 - val_loss: 0.8263 - val_categorical_accuracy: 0.7704 - 1s/epoch - 28ms/step
Epoch 2/1500
51/51 - 0s - loss: 0.8247 - categorical_accuracy: 0.7735 - val_loss: 0.8214 - val_categorical_accuracy: 0.7704 - 490ms/epoch - 10ms/step
Epoch 3/1500
51/51 - 1s - loss: 0.8208 - categorical_accuracy: 0.7735 - val_loss: 0.8178 - val_categorical_accuracy: 0.7704 - 502ms/epoch - 10ms/step
Epoch 4/1500
51/51 - 0s - loss: 0.8143 - categorical_accuracy: 0.7735 - val_loss: 0.8277 - val_categorical_accuracy: 0.7704 - 465ms/epoch - 9ms/step
Epoch 5/1500
51/51 - 0s - loss: 0.8111 - categorical_accuracy: 0.7735 - val_loss: 0.8135 - val_categorical_accuracy: 0.7704 - 489ms/epoch - 10ms/step
Epoch 6/1500
51/51 - 0s - loss: 0.8073 - categorical_accuracy: 0.7735 - val_loss: 0.8072 - val_categorical_accuracy: 0.7704 - 452ms/epoch - 9ms/step
Epoch 7/1500
51/51 - 1s - loss: 0.8027 - categorical_accuracy: 0.7735 - val_loss: 0.8028 - val_categorical_accuracy: 0.7704 - 562ms/epoch - 11ms/step
Epoch 8/1500
51/51 - 0s - loss: 0.8014 - categorical_accuracy: 0.7735 - val_loss: 0.7997 - val_categorical_accuracy: 0.7704 - 452ms/epoch - 9ms/step
Epoch 9/1500
51/51 - 0s - loss: 0.7995 - categorical_accuracy: 0.7735 - val_loss: 0.8131 - val_categorical_accuracy: 0.7704 - 483ms/epoch - 9ms/step
Epoch 10/1500
51/51 - 0s - loss: 0.7903 - categorical_accuracy: 0.7735 - val_loss: 0.7985 - val_categorical_accuracy: 0.7704 - 495ms/epoch - 10ms/step
Epoch 11/1500
51/51 - 0s - loss: 0.7890 - categorical_accuracy: 0.7735 - val_loss: 0.8041 - val_categorical_accuracy: 0.7704 - 491ms/epoch - 10ms/step
Epoch 12/1500
51/51 - 0s - loss: 0.7915 - categorical_accuracy: 0.7735 - val_loss: 0.7889 - val_categorical_accuracy: 0.7704 - 480ms/epoch - 9ms/step
Epoch 13/1500
51/51 - 0s - loss: 0.7801 - categorical_accuracy: 0.7735 - val_loss: 0.7826 - val_categorical_accuracy: 0.7704 - 495ms/epoch - 10ms/step
Epoch 14/1500
51/51 - 0s - loss: 0.7806 - categorical_accuracy: 0.7735 - val_loss: 0.8420 - val_categorical_accuracy: 0.7704 - 489ms/epoch - 10ms/step
Epoch 15/1500
51/51 - 0s - loss: 0.7824 - categorical_accuracy: 0.7735 - val_loss: 0.7843 - val_categorical_accuracy: 0.7704 - 487ms/epoch - 10ms/step
Epoch 16/1500
51/51 - 0s - loss: 0.7726 - categorical_accuracy: 0.7735 - val_loss: 0.7883 - val_categorical_accuracy: 0.7704 - 471ms/epoch - 9ms/step
Epoch 17/1500
51/51 - 0s - loss: 0.7675 - categorical_accuracy: 0.7735 - val_loss: 0.7965 - val_categorical_accuracy: 0.7704 - 472ms/epoch - 9ms/step
Epoch 18/1500
51/51 - 0s - loss: 0.7657 - categorical_accuracy: 0.7735 - val_loss: 0.7703 - val_categorical_accuracy: 0.7704 - 469ms/epoch - 9ms/step
Epoch 19/1500
51/51 - 0s - loss: 0.7644 - categorical_accuracy: 0.7735 - val_loss: 0.8046 - val_categorical_accuracy: 0.7704 - 460ms/epoch - 9ms/step
Epoch 20/1500
51/51 - 0s - loss: 0.7647 - categorical_accuracy: 0.7735 - val_loss: 0.7868 - val_categorical_accuracy: 0.7704 - 476ms/epoch - 9ms/step
Epoch 21/1500
51/51 - 0s - loss: 0.7609 - categorical_accuracy: 0.7734 - val_loss: 0.7658 - val_categorical_accuracy: 0.7704 - 459ms/epoch - 9ms/step
Epoch 22/1500
51/51 - 0s - loss: 0.7572 - categorical_accuracy: 0.7736 - val_loss: 0.7643 - val_categorical_accuracy: 0.7704 - 473ms/epoch - 9ms/step
Epoch 23/1500
51/51 - 0s - loss: 0.7517 - categorical_accuracy: 0.7735 - val_loss: 0.7626 - val_categorical_accuracy: 0.7705 - 460ms/epoch - 9ms/step
Epoch 24/1500
51/51 - 0s - loss: 0.7542 - categorical_accuracy: 0.7736 - val_loss: 0.7564 - val_categorical_accuracy: 0.7706 - 475ms/epoch - 9ms/step
Epoch 25/1500
51/51 - 0s - loss: 0.7455 - categorical_accuracy: 0.7736 - val_loss: 0.7554 - val_categorical_accuracy: 0.7706 - 441ms/epoch - 9ms/step
Epoch 26/1500
51/51 - 0s - loss: 0.7409 - categorical_accuracy: 0.7740 - val_loss: 0.7564 - val_categorical_accuracy: 0.7707 - 490ms/epoch - 10ms/step
Epoch 27/1500
51/51 - 0s - loss: 0.7421 - categorical_accuracy: 0.7737 - val_loss: 0.7934 - val_categorical_accuracy: 0.7704 - 460ms/epoch - 9ms/step
Epoch 28/1500
51/51 - 0s - loss: 0.7413 - categorical_accuracy: 0.7736 - val_loss: 0.7556 - val_categorical_accuracy: 0.7705 - 476ms/epoch - 9ms/step
Epoch 29/1500
51/51 - 0s - loss: 0.7331 - categorical_accuracy: 0.7737 - val_loss: 0.7746 - val_categorical_accuracy: 0.7705 - 443ms/epoch - 9ms/step
Epoch 30/1500
51/51 - 0s - loss: 0.7318 - categorical_accuracy: 0.7755 - val_loss: 0.7538 - val_categorical_accuracy: 0.7712 - 491ms/epoch - 10ms/step
Epoch 31/1500
51/51 - 0s - loss: 0.7255 - categorical_accuracy: 0.7749 - val_loss: 0.7473 - val_categorical_accuracy: 0.7714 - 471ms/epoch - 9ms/step
Epoch 32/1500
51/51 - 0s - loss: 0.7260 - categorical_accuracy: 0.7743 - val_loss: 0.7388 - val_categorical_accuracy: 0.7716 - 463ms/epoch - 9ms/step
Epoch 33/1500
51/51 - 0s - loss: 0.7183 - categorical_accuracy: 0.7756 - val_loss: 0.7385 - val_categorical_accuracy: 0.7718 - 463ms/epoch - 9ms/step
Epoch 34/1500
51/51 - 0s - loss: 0.7148 - categorical_accuracy: 0.7758 - val_loss: 0.7395 - val_categorical_accuracy: 0.7733 - 463ms/epoch - 9ms/step
Epoch 35/1500
51/51 - 0s - loss: 0.7171 - categorical_accuracy: 0.7753 - val_loss: 0.7478 - val_categorical_accuracy: 0.7715 - 463ms/epoch - 9ms/step
Epoch 36/1500
51/51 - 0s - loss: 0.7134 - categorical_accuracy: 0.7749 - val_loss: 0.7398 - val_categorical_accuracy: 0.7721 - 476ms/epoch - 9ms/step
Epoch 37/1500
51/51 - 0s - loss: 0.7059 - categorical_accuracy: 0.7768 - val_loss: 0.7602 - val_categorical_accuracy: 0.7707 - 475ms/epoch - 9ms/step
Epoch 38/1500
51/51 - 0s - loss: 0.7082 - categorical_accuracy: 0.7780 - val_loss: 0.7403 - val_categorical_accuracy: 0.7718 - 458ms/epoch - 9ms/step
Epoch 39/1500
51/51 - 0s - loss: 0.7040 - categorical_accuracy: 0.7774 - val_loss: 0.7370 - val_categorical_accuracy: 0.7732 - 472ms/epoch - 9ms/step
Epoch 40/1500
51/51 - 0s - loss: 0.6934 - categorical_accuracy: 0.7798 - val_loss: 0.7539 - val_categorical_accuracy: 0.7610 - 446ms/epoch - 9ms/step
Epoch 41/1500
51/51 - 0s - loss: 0.6945 - categorical_accuracy: 0.7789 - val_loss: 0.7969 - val_categorical_accuracy: 0.7581 - 491ms/epoch - 10ms/step
Epoch 42/1500
51/51 - 0s - loss: 0.6865 - categorical_accuracy: 0.7800 - val_loss: 0.7273 - val_categorical_accuracy: 0.7751 - 448ms/epoch - 9ms/step
Epoch 43/1500
51/51 - 0s - loss: 0.6985 - categorical_accuracy: 0.7767 - val_loss: 0.7421 - val_categorical_accuracy: 0.7716 - 487ms/epoch - 10ms/step
Epoch 44/1500
51/51 - 0s - loss: 0.6773 - categorical_accuracy: 0.7807 - val_loss: 0.7756 - val_categorical_accuracy: 0.7601 - 444ms/epoch - 9ms/step
Epoch 45/1500
51/51 - 0s - loss: 0.6856 - categorical_accuracy: 0.7806 - val_loss: 0.7305 - val_categorical_accuracy: 0.7732 - 479ms/epoch - 9ms/step
Epoch 46/1500
51/51 - 0s - loss: 0.6800 - categorical_accuracy: 0.7814 - val_loss: 0.7137 - val_categorical_accuracy: 0.7759 - 458ms/epoch - 9ms/step
Epoch 47/1500
51/51 - 0s - loss: 0.6757 - categorical_accuracy: 0.7807 - val_loss: 0.7285 - val_categorical_accuracy: 0.7741 - 493ms/epoch - 10ms/step
Epoch 48/1500
51/51 - 0s - loss: 0.6739 - categorical_accuracy: 0.7823 - val_loss: 0.7056 - val_categorical_accuracy: 0.7784 - 446ms/epoch - 9ms/step
Epoch 49/1500
51/51 - 0s - loss: 0.6709 - categorical_accuracy: 0.7834 - val_loss: 0.7066 - val_categorical_accuracy: 0.7754 - 481ms/epoch - 9ms/step
Epoch 50/1500
51/51 - 0s - loss: 0.6681 - categorical_accuracy: 0.7834 - val_loss: 0.6976 - val_categorical_accuracy: 0.7779 - 462ms/epoch - 9ms/step
Epoch 51/1500
51/51 - 0s - loss: 0.6533 - categorical_accuracy: 0.7875 - val_loss: 0.7073 - val_categorical_accuracy: 0.7760 - 461ms/epoch - 9ms/step
Epoch 52/1500
51/51 - 1s - loss: 0.6657 - categorical_accuracy: 0.7831 - val_loss: 0.7637 - val_categorical_accuracy: 0.7705 - 516ms/epoch - 10ms/step
Epoch 53/1500
51/51 - 0s - loss: 0.6537 - categorical_accuracy: 0.7861 - val_loss: 0.7659 - val_categorical_accuracy: 0.7756 - 462ms/epoch - 9ms/step
Epoch 54/1500
51/51 - 0s - loss: 0.6606 - categorical_accuracy: 0.7852 - val_loss: 0.7193 - val_categorical_accuracy: 0.7774 - 478ms/epoch - 9ms/step
Epoch 55/1500
51/51 - 0s - loss: 0.6516 - categorical_accuracy: 0.7864 - val_loss: 0.7172 - val_categorical_accuracy: 0.7778 - 462ms/epoch - 9ms/step
Epoch 56/1500
51/51 - 0s - loss: 0.6398 - categorical_accuracy: 0.7904 - val_loss: 0.6988 - val_categorical_accuracy: 0.7787 - 475ms/epoch - 9ms/step
Epoch 57/1500
51/51 - 0s - loss: 0.6443 - categorical_accuracy: 0.7882 - val_loss: 0.7480 - val_categorical_accuracy: 0.7743 - 446ms/epoch - 9ms/step
Epoch 58/1500
51/51 - 0s - loss: 0.6417 - categorical_accuracy: 0.7898 - val_loss: 0.7546 - val_categorical_accuracy: 0.7527 - 476ms/epoch - 9ms/step
Epoch 59/1500
51/51 - 0s - loss: 0.6448 - categorical_accuracy: 0.7890 - val_loss: 0.6876 - val_categorical_accuracy: 0.7814 - 445ms/epoch - 9ms/step
Epoch 60/1500
51/51 - 0s - loss: 0.6340 - categorical_accuracy: 0.7884 - val_loss: 0.6955 - val_categorical_accuracy: 0.7759 - 494ms/epoch - 10ms/step
Epoch 61/1500
51/51 - 0s - loss: 0.6278 - categorical_accuracy: 0.7920 - val_loss: 0.6936 - val_categorical_accuracy: 0.7766 - 463ms/epoch - 9ms/step
Epoch 62/1500
51/51 - 0s - loss: 0.6344 - categorical_accuracy: 0.7934 - val_loss: 0.7214 - val_categorical_accuracy: 0.7762 - 490ms/epoch - 10ms/step
Epoch 63/1500
51/51 - 0s - loss: 0.6177 - categorical_accuracy: 0.7948 - val_loss: 0.7087 - val_categorical_accuracy: 0.7781 - 446ms/epoch - 9ms/step
Epoch 64/1500
51/51 - 0s - loss: 0.6232 - categorical_accuracy: 0.7947 - val_loss: 0.7415 - val_categorical_accuracy: 0.7489 - 491ms/epoch - 10ms/step
Epoch 65/1500
51/51 - 0s - loss: 0.6220 - categorical_accuracy: 0.7958 - val_loss: 0.6806 - val_categorical_accuracy: 0.7790 - 473ms/epoch - 9ms/step
Epoch 66/1500
51/51 - 0s - loss: 0.6112 - categorical_accuracy: 0.7952 - val_loss: 0.7400 - val_categorical_accuracy: 0.7510 - 488ms/epoch - 10ms/step
Epoch 67/1500
51/51 - 0s - loss: 0.6156 - categorical_accuracy: 0.7940 - val_loss: 0.7625 - val_categorical_accuracy: 0.7526 - 458ms/epoch - 9ms/step
Epoch 68/1500
51/51 - 0s - loss: 0.6068 - categorical_accuracy: 0.7966 - val_loss: 0.7211 - val_categorical_accuracy: 0.7776 - 474ms/epoch - 9ms/step
Epoch 69/1500
51/51 - 0s - loss: 0.5962 - categorical_accuracy: 0.7995 - val_loss: 0.6806 - val_categorical_accuracy: 0.7763 - 460ms/epoch - 9ms/step
Epoch 70/1500
51/51 - 0s - loss: 0.5989 - categorical_accuracy: 0.7996 - val_loss: 0.6971 - val_categorical_accuracy: 0.7790 - 458ms/epoch - 9ms/step
Epoch 71/1500
51/51 - 0s - loss: 0.5900 - categorical_accuracy: 0.8033 - val_loss: 0.6939 - val_categorical_accuracy: 0.7828 - 476ms/epoch - 9ms/step
Epoch 72/1500
51/51 - 0s - loss: 0.5999 - categorical_accuracy: 0.7991 - val_loss: 0.6750 - val_categorical_accuracy: 0.7847 - 447ms/epoch - 9ms/step
Epoch 73/1500
51/51 - 1s - loss: 0.5795 - categorical_accuracy: 0.8056 - val_loss: 0.6822 - val_categorical_accuracy: 0.7841 - 515ms/epoch - 10ms/step
Epoch 74/1500
51/51 - 1s - loss: 0.5849 - categorical_accuracy: 0.8052 - val_loss: 0.7067 - val_categorical_accuracy: 0.7758 - 524ms/epoch - 10ms/step
Epoch 75/1500
51/51 - 1s - loss: 0.5914 - categorical_accuracy: 0.8023 - val_loss: 0.6920 - val_categorical_accuracy: 0.7785 - 524ms/epoch - 10ms/step
Epoch 76/1500
51/51 - 1s - loss: 0.5857 - categorical_accuracy: 0.7997 - val_loss: 0.6807 - val_categorical_accuracy: 0.7836 - 504ms/epoch - 10ms/step
Epoch 77/1500
51/51 - 1s - loss: 0.5707 - categorical_accuracy: 0.8061 - val_loss: 0.7103 - val_categorical_accuracy: 0.7714 - 505ms/epoch - 10ms/step
Epoch 78/1500
51/51 - 1s - loss: 0.5752 - categorical_accuracy: 0.8075 - val_loss: 0.6710 - val_categorical_accuracy: 0.7858 - 510ms/epoch - 10ms/step
Epoch 79/1500
51/51 - 1s - loss: 0.5671 - categorical_accuracy: 0.8080 - val_loss: 0.6777 - val_categorical_accuracy: 0.7789 - 504ms/epoch - 10ms/step
Epoch 80/1500
51/51 - 1s - loss: 0.5715 - categorical_accuracy: 0.8080 - val_loss: 0.6765 - val_categorical_accuracy: 0.7810 - 524ms/epoch - 10ms/step
Epoch 81/1500
51/51 - 1s - loss: 0.5590 - categorical_accuracy: 0.8123 - val_loss: 0.6888 - val_categorical_accuracy: 0.7851 - 510ms/epoch - 10ms/step
Epoch 82/1500
51/51 - 1s - loss: 0.5628 - categorical_accuracy: 0.8096 - val_loss: 0.7422 - val_categorical_accuracy: 0.7451 - 523ms/epoch - 10ms/step
Epoch 83/1500
51/51 - 1s - loss: 0.5594 - categorical_accuracy: 0.8109 - val_loss: 0.7520 - val_categorical_accuracy: 0.7796 - 508ms/epoch - 10ms/step
Epoch 84/1500
51/51 - 1s - loss: 0.5589 - categorical_accuracy: 0.8088 - val_loss: 0.7086 - val_categorical_accuracy: 0.7631 - 519ms/epoch - 10ms/step
Epoch 85/1500
51/51 - 1s - loss: 0.5488 - categorical_accuracy: 0.8145 - val_loss: 0.6982 - val_categorical_accuracy: 0.7787 - 510ms/epoch - 10ms/step
Epoch 86/1500
51/51 - 1s - loss: 0.5429 - categorical_accuracy: 0.8160 - val_loss: 0.7024 - val_categorical_accuracy: 0.7839 - 537ms/epoch - 11ms/step
Epoch 87/1500
51/51 - 0s - loss: 0.5449 - categorical_accuracy: 0.8144 - val_loss: 0.6661 - val_categorical_accuracy: 0.7892 - 490ms/epoch - 10ms/step
Epoch 88/1500
51/51 - 1s - loss: 0.5446 - categorical_accuracy: 0.8171 - val_loss: 0.7207 - val_categorical_accuracy: 0.7842 - 520ms/epoch - 10ms/step
Epoch 89/1500
51/51 - 0s - loss: 0.5406 - categorical_accuracy: 0.8144 - val_loss: 0.7165 - val_categorical_accuracy: 0.7621 - 492ms/epoch - 10ms/step
Epoch 90/1500
51/51 - 1s - loss: 0.5371 - categorical_accuracy: 0.8176 - val_loss: 0.7334 - val_categorical_accuracy: 0.7472 - 524ms/epoch - 10ms/step
Epoch 91/1500
51/51 - 0s - loss: 0.5417 - categorical_accuracy: 0.8173 - val_loss: 0.6648 - val_categorical_accuracy: 0.7835 - 490ms/epoch - 10ms/step
Epoch 92/1500
51/51 - 1s - loss: 0.5269 - categorical_accuracy: 0.8222 - val_loss: 0.7226 - val_categorical_accuracy: 0.7793 - 554ms/epoch - 11ms/step
Epoch 93/1500
51/51 - 1s - loss: 0.5240 - categorical_accuracy: 0.8212 - val_loss: 0.7429 - val_categorical_accuracy: 0.7440 - 520ms/epoch - 10ms/step
Epoch 94/1500
51/51 - 1s - loss: 0.5300 - categorical_accuracy: 0.8203 - val_loss: 0.6588 - val_categorical_accuracy: 0.7942 - 534ms/epoch - 10ms/step
Epoch 95/1500
51/51 - 0s - loss: 0.5237 - categorical_accuracy: 0.8209 - val_loss: 0.7181 - val_categorical_accuracy: 0.7588 - 491ms/epoch - 10ms/step
Epoch 96/1500
51/51 - 1s - loss: 0.5246 - categorical_accuracy: 0.8199 - val_loss: 0.6984 - val_categorical_accuracy: 0.7634 - 558ms/epoch - 11ms/step
Epoch 97/1500
51/51 - 0s - loss: 0.5104 - categorical_accuracy: 0.8252 - val_loss: 0.7235 - val_categorical_accuracy: 0.7567 - 489ms/epoch - 10ms/step
Epoch 98/1500
51/51 - 1s - loss: 0.5224 - categorical_accuracy: 0.8218 - val_loss: 0.6644 - val_categorical_accuracy: 0.7793 - 546ms/epoch - 11ms/step
Epoch 99/1500
51/51 - 0s - loss: 0.5092 - categorical_accuracy: 0.8252 - val_loss: 0.7975 - val_categorical_accuracy: 0.7703 - 488ms/epoch - 10ms/step
Epoch 100/1500
51/51 - 1s - loss: 0.5217 - categorical_accuracy: 0.8232 - val_loss: 0.6553 - val_categorical_accuracy: 0.7867 - 523ms/epoch - 10ms/step
Epoch 101/1500
51/51 - 1s - loss: 0.4929 - categorical_accuracy: 0.8296 - val_loss: 0.6759 - val_categorical_accuracy: 0.7836 - 504ms/epoch - 10ms/step
Epoch 102/1500
51/51 - 1s - loss: 0.5116 - categorical_accuracy: 0.8252 - val_loss: 0.7371 - val_categorical_accuracy: 0.7597 - 524ms/epoch - 10ms/step
Epoch 103/1500
51/51 - 1s - loss: 0.4980 - categorical_accuracy: 0.8306 - val_loss: 0.6913 - val_categorical_accuracy: 0.7839 - 507ms/epoch - 10ms/step
Epoch 104/1500
51/51 - 1s - loss: 0.5035 - categorical_accuracy: 0.8301 - val_loss: 0.7065 - val_categorical_accuracy: 0.7884 - 519ms/epoch - 10ms/step
Epoch 105/1500
51/51 - 1s - loss: 0.4908 - categorical_accuracy: 0.8321 - val_loss: 0.7398 - val_categorical_accuracy: 0.7721 - 507ms/epoch - 10ms/step
Epoch 106/1500
51/51 - 1s - loss: 0.4907 - categorical_accuracy: 0.8297 - val_loss: 0.6861 - val_categorical_accuracy: 0.7753 - 508ms/epoch - 10ms/step
Epoch 107/1500
51/51 - 0s - loss: 0.4965 - categorical_accuracy: 0.8299 - val_loss: 0.6716 - val_categorical_accuracy: 0.7890 - 487ms/epoch - 10ms/step
Epoch 108/1500
51/51 - 1s - loss: 0.4919 - categorical_accuracy: 0.8328 - val_loss: 0.6664 - val_categorical_accuracy: 0.7883 - 509ms/epoch - 10ms/step
Epoch 109/1500
51/51 - 1s - loss: 0.4918 - categorical_accuracy: 0.8300 - val_loss: 0.6663 - val_categorical_accuracy: 0.7882 - 522ms/epoch - 10ms/step
Epoch 110/1500
51/51 - 1s - loss: 0.4756 - categorical_accuracy: 0.8376 - val_loss: 0.7065 - val_categorical_accuracy: 0.7787 - 509ms/epoch - 10ms/step
Epoch 111/1500
51/51 - 0s - loss: 0.4872 - categorical_accuracy: 0.8336 - val_loss: 0.6887 - val_categorical_accuracy: 0.7886 - 499ms/epoch - 10ms/step
Epoch 112/1500
51/51 - 1s - loss: 0.4830 - categorical_accuracy: 0.8352 - val_loss: 0.6729 - val_categorical_accuracy: 0.7898 - 532ms/epoch - 10ms/step
Epoch 113/1500
51/51 - 1s - loss: 0.4687 - categorical_accuracy: 0.8375 - val_loss: 0.8141 - val_categorical_accuracy: 0.7751 - 504ms/epoch - 10ms/step
Epoch 114/1500
51/51 - 1s - loss: 0.4789 - categorical_accuracy: 0.8365 - val_loss: 0.7049 - val_categorical_accuracy: 0.7905 - 510ms/epoch - 10ms/step
Epoch 115/1500
51/51 - 1s - loss: 0.4661 - categorical_accuracy: 0.8391 - val_loss: 0.6839 - val_categorical_accuracy: 0.7814 - 509ms/epoch - 10ms/step
Epoch 116/1500
51/51 - 1s - loss: 0.4723 - categorical_accuracy: 0.8363 - val_loss: 0.7646 - val_categorical_accuracy: 0.7782 - 511ms/epoch - 10ms/step
Epoch 117/1500
51/51 - 1s - loss: 0.4682 - categorical_accuracy: 0.8379 - val_loss: 0.7473 - val_categorical_accuracy: 0.7612 - 519ms/epoch - 10ms/step
Epoch 118/1500
51/51 - 1s - loss: 0.4643 - categorical_accuracy: 0.8395 - val_loss: 0.7271 - val_categorical_accuracy: 0.7490 - 510ms/epoch - 10ms/step
Epoch 119/1500
51/51 - 1s - loss: 0.4539 - categorical_accuracy: 0.8426 - val_loss: 0.7771 - val_categorical_accuracy: 0.7455 - 539ms/epoch - 11ms/step
Epoch 120/1500
51/51 - 1s - loss: 0.4706 - categorical_accuracy: 0.8368 - val_loss: 0.6617 - val_categorical_accuracy: 0.7960 - 522ms/epoch - 10ms/step
Epoch 121/1500
51/51 - 1s - loss: 0.4646 - categorical_accuracy: 0.8376 - val_loss: 0.7861 - val_categorical_accuracy: 0.7870 - 555ms/epoch - 11ms/step
Epoch 122/1500
51/51 - 0s - loss: 0.4488 - categorical_accuracy: 0.8442 - val_loss: 0.7719 - val_categorical_accuracy: 0.7879 - 496ms/epoch - 10ms/step
Epoch 123/1500
51/51 - 1s - loss: 0.4561 - categorical_accuracy: 0.8417 - val_loss: 0.7538 - val_categorical_accuracy: 0.7904 - 527ms/epoch - 10ms/step
Epoch 124/1500
51/51 - 0s - loss: 0.4640 - categorical_accuracy: 0.8404 - val_loss: 0.6697 - val_categorical_accuracy: 0.7862 - 490ms/epoch - 10ms/step
Epoch 125/1500
51/51 - 0s - loss: 0.4474 - categorical_accuracy: 0.8438 - val_loss: 0.6495 - val_categorical_accuracy: 0.7906 - 494ms/epoch - 10ms/step
Epoch 126/1500
51/51 - 1s - loss: 0.4374 - categorical_accuracy: 0.8476 - val_loss: 0.7306 - val_categorical_accuracy: 0.7629 - 536ms/epoch - 11ms/step
Epoch 127/1500
51/51 - 1s - loss: 0.4485 - categorical_accuracy: 0.8431 - val_loss: 0.6888 - val_categorical_accuracy: 0.7711 - 547ms/epoch - 11ms/step
Epoch 128/1500
51/51 - 1s - loss: 0.4492 - categorical_accuracy: 0.8452 - val_loss: 0.6952 - val_categorical_accuracy: 0.7702 - 553ms/epoch - 11ms/step
Epoch 129/1500
51/51 - 1s - loss: 0.4419 - categorical_accuracy: 0.8478 - val_loss: 0.6953 - val_categorical_accuracy: 0.7721 - 561ms/epoch - 11ms/step
Epoch 130/1500
51/51 - 1s - loss: 0.4347 - categorical_accuracy: 0.8484 - val_loss: 0.6821 - val_categorical_accuracy: 0.7774 - 557ms/epoch - 11ms/step
Epoch 131/1500
51/51 - 1s - loss: 0.4321 - categorical_accuracy: 0.8485 - val_loss: 0.7041 - val_categorical_accuracy: 0.7824 - 567ms/epoch - 11ms/step
Epoch 132/1500
51/51 - 1s - loss: 0.4422 - categorical_accuracy: 0.8457 - val_loss: 0.6702 - val_categorical_accuracy: 0.7909 - 558ms/epoch - 11ms/step
Epoch 133/1500
51/51 - 1s - loss: 0.4326 - categorical_accuracy: 0.8484 - val_loss: 0.7774 - val_categorical_accuracy: 0.7793 - 547ms/epoch - 11ms/step
Epoch 134/1500
51/51 - 1s - loss: 0.4297 - categorical_accuracy: 0.8518 - val_loss: 0.8498 - val_categorical_accuracy: 0.7841 - 573ms/epoch - 11ms/step
Epoch 135/1500
51/51 - 1s - loss: 0.4408 - categorical_accuracy: 0.8469 - val_loss: 0.6671 - val_categorical_accuracy: 0.7876 - 524ms/epoch - 10ms/step
Epoch 136/1500
51/51 - 1s - loss: 0.4252 - categorical_accuracy: 0.8526 - val_loss: 0.7461 - val_categorical_accuracy: 0.7557 - 556ms/epoch - 11ms/step
Epoch 137/1500
51/51 - 1s - loss: 0.4217 - categorical_accuracy: 0.8527 - val_loss: 0.6965 - val_categorical_accuracy: 0.7742 - 540ms/epoch - 11ms/step
Epoch 138/1500
51/51 - 1s - loss: 0.4187 - categorical_accuracy: 0.8539 - val_loss: 0.6703 - val_categorical_accuracy: 0.7988 - 570ms/epoch - 11ms/step
Epoch 139/1500
51/51 - 1s - loss: 0.4260 - categorical_accuracy: 0.8521 - val_loss: 0.7349 - val_categorical_accuracy: 0.7602 - 540ms/epoch - 11ms/step
Epoch 140/1500
51/51 - 1s - loss: 0.4119 - categorical_accuracy: 0.8575 - val_loss: 0.6754 - val_categorical_accuracy: 0.7910 - 555ms/epoch - 11ms/step
Epoch 141/1500
51/51 - 1s - loss: 0.4006 - categorical_accuracy: 0.8594 - val_loss: 0.7313 - val_categorical_accuracy: 0.7641 - 557ms/epoch - 11ms/step
Epoch 142/1500
51/51 - 1s - loss: 0.4197 - categorical_accuracy: 0.8524 - val_loss: 0.7658 - val_categorical_accuracy: 0.7463 - 524ms/epoch - 10ms/step
Epoch 143/1500
51/51 - 1s - loss: 0.4115 - categorical_accuracy: 0.8556 - val_loss: 0.7072 - val_categorical_accuracy: 0.7857 - 571ms/epoch - 11ms/step
Epoch 144/1500
51/51 - 1s - loss: 0.4077 - categorical_accuracy: 0.8578 - val_loss: 0.6732 - val_categorical_accuracy: 0.7931 - 527ms/epoch - 10ms/step
Epoch 145/1500
51/51 - 1s - loss: 0.4066 - categorical_accuracy: 0.8580 - val_loss: 0.7057 - val_categorical_accuracy: 0.7799 - 574ms/epoch - 11ms/step
Epoch 146/1500
51/51 - 1s - loss: 0.4136 - categorical_accuracy: 0.8544 - val_loss: 0.7142 - val_categorical_accuracy: 0.7987 - 536ms/epoch - 11ms/step
Epoch 147/1500
51/51 - 1s - loss: 0.4065 - categorical_accuracy: 0.8581 - val_loss: 0.7012 - val_categorical_accuracy: 0.7979 - 567ms/epoch - 11ms/step
Epoch 148/1500
51/51 - 1s - loss: 0.4020 - categorical_accuracy: 0.8572 - val_loss: 0.7168 - val_categorical_accuracy: 0.7824 - 536ms/epoch - 11ms/step
Epoch 149/1500
51/51 - 1s - loss: 0.4101 - categorical_accuracy: 0.8552 - val_loss: 0.6899 - val_categorical_accuracy: 0.7958 - 595ms/epoch - 12ms/step
Epoch 150/1500
51/51 - 1s - loss: 0.3965 - categorical_accuracy: 0.8628 - val_loss: 0.6940 - val_categorical_accuracy: 0.7989 - 555ms/epoch - 11ms/step
Epoch 151/1500
51/51 - 1s - loss: 0.3901 - categorical_accuracy: 0.8645 - val_loss: 0.7035 - val_categorical_accuracy: 0.7852 - 535ms/epoch - 10ms/step
Epoch 152/1500
51/51 - 1s - loss: 0.3946 - categorical_accuracy: 0.8624 - val_loss: 0.8069 - val_categorical_accuracy: 0.7310 - 536ms/epoch - 11ms/step
Epoch 153/1500
51/51 - 0s - loss: 0.3896 - categorical_accuracy: 0.8647 - val_loss: 0.7703 - val_categorical_accuracy: 0.7707 - 493ms/epoch - 10ms/step
Epoch 154/1500
51/51 - 1s - loss: 0.3946 - categorical_accuracy: 0.8617 - val_loss: 0.7686 - val_categorical_accuracy: 0.7596 - 522ms/epoch - 10ms/step
Epoch 155/1500
51/51 - 0s - loss: 0.3915 - categorical_accuracy: 0.8619 - val_loss: 0.7009 - val_categorical_accuracy: 0.7973 - 478ms/epoch - 9ms/step
Epoch 156/1500
51/51 - 1s - loss: 0.3825 - categorical_accuracy: 0.8661 - val_loss: 0.7232 - val_categorical_accuracy: 0.7928 - 522ms/epoch - 10ms/step
Epoch 157/1500
51/51 - 0s - loss: 0.3876 - categorical_accuracy: 0.8623 - val_loss: 0.7051 - val_categorical_accuracy: 0.7915 - 500ms/epoch - 10ms/step
Epoch 158/1500
51/51 - 1s - loss: 0.3777 - categorical_accuracy: 0.8657 - val_loss: 0.7299 - val_categorical_accuracy: 0.7949 - 506ms/epoch - 10ms/step
Epoch 159/1500
51/51 - 0s - loss: 0.3845 - categorical_accuracy: 0.8665 - val_loss: 0.7123 - val_categorical_accuracy: 0.7905 - 489ms/epoch - 10ms/step
Epoch 160/1500
51/51 - 1s - loss: 0.3696 - categorical_accuracy: 0.8715 - val_loss: 0.7486 - val_categorical_accuracy: 0.7723 - 520ms/epoch - 10ms/step
Epoch 161/1500
51/51 - 0s - loss: 0.3737 - categorical_accuracy: 0.8666 - val_loss: 0.8908 - val_categorical_accuracy: 0.6961 - 489ms/epoch - 10ms/step
Epoch 162/1500
51/51 - 1s - loss: 0.3851 - categorical_accuracy: 0.8638 - val_loss: 0.7011 - val_categorical_accuracy: 0.7918 - 537ms/epoch - 11ms/step
Epoch 163/1500
51/51 - 1s - loss: 0.3639 - categorical_accuracy: 0.8714 - val_loss: 0.7187 - val_categorical_accuracy: 0.7958 - 509ms/epoch - 10ms/step
Epoch 164/1500
51/51 - 1s - loss: 0.3654 - categorical_accuracy: 0.8718 - val_loss: 0.7134 - val_categorical_accuracy: 0.7964 - 505ms/epoch - 10ms/step
Epoch 165/1500
51/51 - 0s - loss: 0.3692 - categorical_accuracy: 0.8689 - val_loss: 0.8419 - val_categorical_accuracy: 0.7956 - 494ms/epoch - 10ms/step
Epoch 166/1500
51/51 - 1s - loss: 0.3850 - categorical_accuracy: 0.8645 - val_loss: 0.6888 - val_categorical_accuracy: 0.7957 - 522ms/epoch - 10ms/step
Epoch 167/1500
51/51 - 0s - loss: 0.3729 - categorical_accuracy: 0.8662 - val_loss: 0.7192 - val_categorical_accuracy: 0.8008 - 480ms/epoch - 9ms/step
Epoch 168/1500
51/51 - 1s - loss: 0.3522 - categorical_accuracy: 0.8756 - val_loss: 0.8288 - val_categorical_accuracy: 0.7977 - 529ms/epoch - 10ms/step
Epoch 169/1500
51/51 - 1s - loss: 0.3580 - categorical_accuracy: 0.8738 - val_loss: 0.9097 - val_categorical_accuracy: 0.7926 - 506ms/epoch - 10ms/step
Epoch 170/1500
51/51 - 1s - loss: 0.3648 - categorical_accuracy: 0.8684 - val_loss: 0.7377 - val_categorical_accuracy: 0.7998 - 540ms/epoch - 11ms/step
Epoch 171/1500
51/51 - 0s - loss: 0.3569 - categorical_accuracy: 0.8727 - val_loss: 0.7504 - val_categorical_accuracy: 0.7751 - 493ms/epoch - 10ms/step
Epoch 172/1500
51/51 - 1s - loss: 0.3721 - categorical_accuracy: 0.8677 - val_loss: 0.7101 - val_categorical_accuracy: 0.8009 - 506ms/epoch - 10ms/step
Epoch 173/1500
51/51 - 0s - loss: 0.3526 - categorical_accuracy: 0.8737 - val_loss: 0.7818 - val_categorical_accuracy: 0.7927 - 494ms/epoch - 10ms/step
Epoch 174/1500
51/51 - 1s - loss: 0.3597 - categorical_accuracy: 0.8723 - val_loss: 0.7407 - val_categorical_accuracy: 0.7940 - 527ms/epoch - 10ms/step
Epoch 175/1500
51/51 - 0s - loss: 0.3494 - categorical_accuracy: 0.8755 - val_loss: 0.7040 - val_categorical_accuracy: 0.7943 - 494ms/epoch - 10ms/step
Epoch 176/1500
51/51 - 1s - loss: 0.3440 - categorical_accuracy: 0.8786 - val_loss: 0.7636 - val_categorical_accuracy: 0.7716 - 520ms/epoch - 10ms/step
Epoch 177/1500
51/51 - 1s - loss: 0.3384 - categorical_accuracy: 0.8794 - val_loss: 0.8116 - val_categorical_accuracy: 0.7927 - 508ms/epoch - 10ms/step
Epoch 178/1500
51/51 - 1s - loss: 0.3502 - categorical_accuracy: 0.8766 - val_loss: 0.7352 - val_categorical_accuracy: 0.7874 - 500ms/epoch - 10ms/step
Epoch 179/1500
51/51 - 0s - loss: 0.3436 - categorical_accuracy: 0.8772 - val_loss: 0.7792 - val_categorical_accuracy: 0.7995 - 492ms/epoch - 10ms/step
Epoch 180/1500
51/51 - 1s - loss: 0.3390 - categorical_accuracy: 0.8787 - val_loss: 0.7295 - val_categorical_accuracy: 0.7839 - 516ms/epoch - 10ms/step
Epoch 181/1500
51/51 - 1s - loss: 0.3453 - categorical_accuracy: 0.8749 - val_loss: 0.7225 - val_categorical_accuracy: 0.7999 - 509ms/epoch - 10ms/step
Epoch 182/1500
51/51 - 1s - loss: 0.3401 - categorical_accuracy: 0.8768 - val_loss: 0.7885 - val_categorical_accuracy: 0.7947 - 503ms/epoch - 10ms/step
Epoch 183/1500
51/51 - 1s - loss: 0.3431 - categorical_accuracy: 0.8779 - val_loss: 0.8370 - val_categorical_accuracy: 0.7933 - 511ms/epoch - 10ms/step
Epoch 184/1500
51/51 - 0s - loss: 0.3435 - categorical_accuracy: 0.8761 - val_loss: 0.7499 - val_categorical_accuracy: 0.7966 - 485ms/epoch - 10ms/step
Epoch 185/1500
51/51 - 1s - loss: 0.3365 - categorical_accuracy: 0.8794 - val_loss: 0.7274 - val_categorical_accuracy: 0.7963 - 524ms/epoch - 10ms/step
Epoch 186/1500
51/51 - 1s - loss: 0.3290 - categorical_accuracy: 0.8820 - val_loss: 0.7467 - val_categorical_accuracy: 0.7935 - 506ms/epoch - 10ms/step
Epoch 187/1500
51/51 - 1s - loss: 0.3241 - categorical_accuracy: 0.8836 - val_loss: 0.7447 - val_categorical_accuracy: 0.8007 - 555ms/epoch - 11ms/step
Epoch 188/1500
51/51 - 1s - loss: 0.3273 - categorical_accuracy: 0.8822 - val_loss: 0.7845 - val_categorical_accuracy: 0.7862 - 553ms/epoch - 11ms/step
Epoch 189/1500
51/51 - 1s - loss: 0.3251 - categorical_accuracy: 0.8842 - val_loss: 0.7280 - val_categorical_accuracy: 0.7958 - 550ms/epoch - 11ms/step
Epoch 190/1500
51/51 - 0s - loss: 0.3268 - categorical_accuracy: 0.8832 - val_loss: 0.8024 - val_categorical_accuracy: 0.7651 - 487ms/epoch - 10ms/step
Epoch 191/1500
51/51 - 1s - loss: 0.3295 - categorical_accuracy: 0.8814 - val_loss: 0.7832 - val_categorical_accuracy: 0.8012 - 533ms/epoch - 10ms/step
Epoch 192/1500
51/51 - 0s - loss: 0.3287 - categorical_accuracy: 0.8828 - val_loss: 0.7740 - val_categorical_accuracy: 0.7989 - 494ms/epoch - 10ms/step
Epoch 193/1500
51/51 - 1s - loss: 0.3304 - categorical_accuracy: 0.8818 - val_loss: 0.7983 - val_categorical_accuracy: 0.7874 - 519ms/epoch - 10ms/step
Epoch 194/1500
51/51 - 0s - loss: 0.3298 - categorical_accuracy: 0.8822 - val_loss: 0.7375 - val_categorical_accuracy: 0.7983 - 489ms/epoch - 10ms/step
Epoch 195/1500
51/51 - 1s - loss: 0.3159 - categorical_accuracy: 0.8866 - val_loss: 0.7725 - val_categorical_accuracy: 0.7851 - 548ms/epoch - 11ms/step
Epoch 196/1500
51/51 - 1s - loss: 0.3143 - categorical_accuracy: 0.8880 - val_loss: 0.8097 - val_categorical_accuracy: 0.7822 - 517ms/epoch - 10ms/step
Epoch 197/1500
51/51 - 1s - loss: 0.3284 - categorical_accuracy: 0.8811 - val_loss: 0.7964 - val_categorical_accuracy: 0.8015 - 525ms/epoch - 10ms/step
Epoch 198/1500
51/51 - 0s - loss: 0.3429 - categorical_accuracy: 0.8745 - val_loss: 0.7824 - val_categorical_accuracy: 0.7659 - 489ms/epoch - 10ms/step
Epoch 199/1500
51/51 - 1s - loss: 0.2947 - categorical_accuracy: 0.8942 - val_loss: 0.8137 - val_categorical_accuracy: 0.8040 - 539ms/epoch - 11ms/step
Epoch 200/1500
51/51 - 0s - loss: 0.3165 - categorical_accuracy: 0.8864 - val_loss: 0.7691 - val_categorical_accuracy: 0.7981 - 493ms/epoch - 10ms/step
Epoch 201/1500
51/51 - 1s - loss: 0.3032 - categorical_accuracy: 0.8905 - val_loss: 0.8096 - val_categorical_accuracy: 0.7873 - 521ms/epoch - 10ms/step
Epoch 202/1500
51/51 - 0s - loss: 0.3023 - categorical_accuracy: 0.8914 - val_loss: 0.8817 - val_categorical_accuracy: 0.7904 - 476ms/epoch - 9ms/step
Epoch 203/1500
51/51 - 1s - loss: 0.3118 - categorical_accuracy: 0.8867 - val_loss: 0.7608 - val_categorical_accuracy: 0.7949 - 510ms/epoch - 10ms/step
Epoch 204/1500
51/51 - 0s - loss: 0.3146 - categorical_accuracy: 0.8888 - val_loss: 0.8212 - val_categorical_accuracy: 0.7874 - 492ms/epoch - 10ms/step
Epoch 205/1500
51/51 - 1s - loss: 0.2972 - categorical_accuracy: 0.8934 - val_loss: 0.8137 - val_categorical_accuracy: 0.7974 - 510ms/epoch - 10ms/step
Epoch 206/1500
51/51 - 0s - loss: 0.3017 - categorical_accuracy: 0.8914 - val_loss: 0.8625 - val_categorical_accuracy: 0.7648 - 492ms/epoch - 10ms/step
Epoch 207/1500
51/51 - 1s - loss: 0.3133 - categorical_accuracy: 0.8871 - val_loss: 0.8011 - val_categorical_accuracy: 0.7969 - 535ms/epoch - 10ms/step
Epoch 208/1500
51/51 - 1s - loss: 0.3115 - categorical_accuracy: 0.8879 - val_loss: 0.8100 - val_categorical_accuracy: 0.7843 - 502ms/epoch - 10ms/step
Epoch 209/1500
51/51 - 1s - loss: 0.2903 - categorical_accuracy: 0.8953 - val_loss: 0.8007 - val_categorical_accuracy: 0.7963 - 541ms/epoch - 11ms/step
Epoch 210/1500
51/51 - 0s - loss: 0.3270 - categorical_accuracy: 0.8840 - val_loss: 0.8345 - val_categorical_accuracy: 0.7987 - 496ms/epoch - 10ms/step
Epoch 211/1500
51/51 - 1s - loss: 0.3085 - categorical_accuracy: 0.8883 - val_loss: 0.8033 - val_categorical_accuracy: 0.8018 - 581ms/epoch - 11ms/step
Epoch 212/1500
51/51 - 1s - loss: 0.2839 - categorical_accuracy: 0.8976 - val_loss: 0.8398 - val_categorical_accuracy: 0.7769 - 551ms/epoch - 11ms/step
Epoch 213/1500
51/51 - 1s - loss: 0.2961 - categorical_accuracy: 0.8939 - val_loss: 0.7720 - val_categorical_accuracy: 0.7994 - 517ms/epoch - 10ms/step
Epoch 214/1500
51/51 - 1s - loss: 0.3032 - categorical_accuracy: 0.8915 - val_loss: 0.8151 - val_categorical_accuracy: 0.7949 - 568ms/epoch - 11ms/step
Epoch 215/1500
51/51 - 1s - loss: 0.2735 - categorical_accuracy: 0.9044 - val_loss: 0.8520 - val_categorical_accuracy: 0.7998 - 558ms/epoch - 11ms/step
Epoch 216/1500
51/51 - 1s - loss: 0.3091 - categorical_accuracy: 0.8885 - val_loss: 0.7748 - val_categorical_accuracy: 0.8018 - 535ms/epoch - 10ms/step
Epoch 217/1500
51/51 - 0s - loss: 0.2907 - categorical_accuracy: 0.8980 - val_loss: 0.7571 - val_categorical_accuracy: 0.7969 - 490ms/epoch - 10ms/step
Epoch 218/1500
51/51 - 1s - loss: 0.2805 - categorical_accuracy: 0.8973 - val_loss: 0.8165 - val_categorical_accuracy: 0.7930 - 561ms/epoch - 11ms/step
Epoch 219/1500
51/51 - 1s - loss: 0.2957 - categorical_accuracy: 0.8929 - val_loss: 0.7899 - val_categorical_accuracy: 0.8000 - 504ms/epoch - 10ms/step
Epoch 220/1500
51/51 - 1s - loss: 0.2885 - categorical_accuracy: 0.8972 - val_loss: 0.9645 - val_categorical_accuracy: 0.7904 - 537ms/epoch - 11ms/step
Epoch 221/1500
51/51 - 0s - loss: 0.2934 - categorical_accuracy: 0.8944 - val_loss: 0.8398 - val_categorical_accuracy: 0.7807 - 500ms/epoch - 10ms/step
Epoch 222/1500
51/51 - 1s - loss: 0.3033 - categorical_accuracy: 0.8907 - val_loss: 0.8211 - val_categorical_accuracy: 0.7917 - 519ms/epoch - 10ms/step
Epoch 223/1500
51/51 - 1s - loss: 0.2727 - categorical_accuracy: 0.9005 - val_loss: 0.8128 - val_categorical_accuracy: 0.7998 - 508ms/epoch - 10ms/step
Epoch 224/1500
51/51 - 1s - loss: 0.2911 - categorical_accuracy: 0.8954 - val_loss: 0.8360 - val_categorical_accuracy: 0.8043 - 523ms/epoch - 10ms/step
Epoch 225/1500
51/51 - 0s - loss: 0.2616 - categorical_accuracy: 0.9055 - val_loss: 0.8339 - val_categorical_accuracy: 0.7969 - 499ms/epoch - 10ms/step
Epoch 226/1500
51/51 - 1s - loss: 0.2786 - categorical_accuracy: 0.8968 - val_loss: 0.8420 - val_categorical_accuracy: 0.7829 - 542ms/epoch - 11ms/step
Epoch 227/1500
51/51 - 1s - loss: 0.2670 - categorical_accuracy: 0.9040 - val_loss: 0.8483 - val_categorical_accuracy: 0.8005 - 515ms/epoch - 10ms/step
Epoch 228/1500
51/51 - 1s - loss: 0.2751 - categorical_accuracy: 0.9009 - val_loss: 1.1463 - val_categorical_accuracy: 0.7835 - 548ms/epoch - 11ms/step
Epoch 229/1500
51/51 - 1s - loss: 0.2797 - categorical_accuracy: 0.8993 - val_loss: 1.3415 - val_categorical_accuracy: 0.6515 - 590ms/epoch - 12ms/step
Epoch 230/1500
51/51 - 0s - loss: 0.3131 - categorical_accuracy: 0.8917 - val_loss: 0.8274 - val_categorical_accuracy: 0.7871 - 494ms/epoch - 10ms/step
Epoch 231/1500
51/51 - 1s - loss: 0.2772 - categorical_accuracy: 0.8996 - val_loss: 0.8547 - val_categorical_accuracy: 0.7800 - 520ms/epoch - 10ms/step
Epoch 232/1500
51/51 - 1s - loss: 0.2820 - categorical_accuracy: 0.8979 - val_loss: 0.8272 - val_categorical_accuracy: 0.7829 - 540ms/epoch - 11ms/step
Epoch 233/1500
51/51 - 1s - loss: 0.2754 - categorical_accuracy: 0.9014 - val_loss: 0.8432 - val_categorical_accuracy: 0.7795 - 540ms/epoch - 11ms/step
Epoch 234/1500
51/51 - 1s - loss: 0.2585 - categorical_accuracy: 0.9066 - val_loss: 0.9509 - val_categorical_accuracy: 0.7564 - 587ms/epoch - 12ms/step
Epoch 235/1500
51/51 - 1s - loss: 0.2664 - categorical_accuracy: 0.9046 - val_loss: 0.8392 - val_categorical_accuracy: 0.7966 - 549ms/epoch - 11ms/step
Epoch 236/1500
51/51 - 0s - loss: 0.2685 - categorical_accuracy: 0.9048 - val_loss: 0.9728 - val_categorical_accuracy: 0.7335 - 487ms/epoch - 10ms/step
Epoch 237/1500
51/51 - 1s - loss: 0.2604 - categorical_accuracy: 0.9060 - val_loss: 0.9428 - val_categorical_accuracy: 0.7740 - 503ms/epoch - 10ms/step
Epoch 238/1500
51/51 - 0s - loss: 0.2640 - categorical_accuracy: 0.9023 - val_loss: 0.9071 - val_categorical_accuracy: 0.7961 - 494ms/epoch - 10ms/step
Epoch 239/1500
51/51 - 1s - loss: 0.2610 - categorical_accuracy: 0.9048 - val_loss: 0.9489 - val_categorical_accuracy: 0.8017 - 584ms/epoch - 11ms/step
Epoch 240/1500
51/51 - 1s - loss: 0.2857 - categorical_accuracy: 0.8994 - val_loss: 0.8291 - val_categorical_accuracy: 0.7932 - 522ms/epoch - 10ms/step
Epoch 241/1500
51/51 - 1s - loss: 0.2434 - categorical_accuracy: 0.9118 - val_loss: 0.9963 - val_categorical_accuracy: 0.7576 - 575ms/epoch - 11ms/step
Epoch 242/1500
51/51 - 0s - loss: 0.2579 - categorical_accuracy: 0.9058 - val_loss: 0.8447 - val_categorical_accuracy: 0.7943 - 460ms/epoch - 9ms/step
Epoch 243/1500
51/51 - 0s - loss: 0.2492 - categorical_accuracy: 0.9098 - val_loss: 0.9187 - val_categorical_accuracy: 0.7923 - 490ms/epoch - 10ms/step
Epoch 244/1500
51/51 - 0s - loss: 0.2815 - categorical_accuracy: 0.8998 - val_loss: 0.8295 - val_categorical_accuracy: 0.8044 - 454ms/epoch - 9ms/step
Epoch 245/1500
51/51 - 1s - loss: 0.2718 - categorical_accuracy: 0.9021 - val_loss: 0.8966 - val_categorical_accuracy: 0.8022 - 530ms/epoch - 10ms/step
Epoch 246/1500
51/51 - 0s - loss: 0.2428 - categorical_accuracy: 0.9125 - val_loss: 0.8394 - val_categorical_accuracy: 0.7994 - 460ms/epoch - 9ms/step
Epoch 247/1500
51/51 - 0s - loss: 0.2499 - categorical_accuracy: 0.9105 - val_loss: 0.9993 - val_categorical_accuracy: 0.7111 - 493ms/epoch - 10ms/step
Epoch 248/1500
51/51 - 0s - loss: 0.2374 - categorical_accuracy: 0.9137 - val_loss: 0.9173 - val_categorical_accuracy: 0.8028 - 457ms/epoch - 9ms/step
Epoch 249/1500
51/51 - 0s - loss: 0.2799 - categorical_accuracy: 0.8981 - val_loss: 0.8828 - val_categorical_accuracy: 0.7975 - 493ms/epoch - 10ms/step
Epoch 250/1500
51/51 - 0s - loss: 0.2621 - categorical_accuracy: 0.9032 - val_loss: 0.9809 - val_categorical_accuracy: 0.7787 - 464ms/epoch - 9ms/step
Epoch 251/1500
51/51 - 0s - loss: 0.2376 - categorical_accuracy: 0.9135 - val_loss: 1.0136 - val_categorical_accuracy: 0.7366 - 490ms/epoch - 10ms/step
Epoch 252/1500
51/51 - 0s - loss: 0.2588 - categorical_accuracy: 0.9059 - val_loss: 0.9361 - val_categorical_accuracy: 0.8056 - 478ms/epoch - 9ms/step
Epoch 253/1500
51/51 - 1s - loss: 0.2346 - categorical_accuracy: 0.9142 - val_loss: 0.8899 - val_categorical_accuracy: 0.8034 - 520ms/epoch - 10ms/step
Epoch 254/1500
51/51 - 0s - loss: 0.2818 - categorical_accuracy: 0.9001 - val_loss: 0.8544 - val_categorical_accuracy: 0.7938 - 480ms/epoch - 9ms/step
Epoch 255/1500
51/51 - 1s - loss: 0.2279 - categorical_accuracy: 0.9162 - val_loss: 0.9075 - val_categorical_accuracy: 0.8007 - 505ms/epoch - 10ms/step
Epoch 256/1500
51/51 - 0s - loss: 0.2410 - categorical_accuracy: 0.9111 - val_loss: 0.8986 - val_categorical_accuracy: 0.8057 - 480ms/epoch - 9ms/step
Epoch 257/1500
51/51 - 0s - loss: 0.2429 - categorical_accuracy: 0.9106 - val_loss: 0.8849 - val_categorical_accuracy: 0.7875 - 490ms/epoch - 10ms/step
Epoch 258/1500
51/51 - 1s - loss: 0.2417 - categorical_accuracy: 0.9118 - val_loss: 1.4033 - val_categorical_accuracy: 0.7814 - 560ms/epoch - 11ms/step
Epoch 259/1500
51/51 - 1s - loss: 0.2615 - categorical_accuracy: 0.9068 - val_loss: 0.9780 - val_categorical_accuracy: 0.7959 - 572ms/epoch - 11ms/step
Epoch 260/1500
51/51 - 1s - loss: 0.2455 - categorical_accuracy: 0.9089 - val_loss: 0.9119 - val_categorical_accuracy: 0.8043 - 503ms/epoch - 10ms/step
Epoch 261/1500
51/51 - 1s - loss: 0.2204 - categorical_accuracy: 0.9200 - val_loss: 0.9365 - val_categorical_accuracy: 0.7797 - 529ms/epoch - 10ms/step
Epoch 262/1500
51/51 - 0s - loss: 0.2716 - categorical_accuracy: 0.9011 - val_loss: 0.8973 - val_categorical_accuracy: 0.7829 - 480ms/epoch - 9ms/step
Epoch 263/1500
51/51 - 0s - loss: 0.2201 - categorical_accuracy: 0.9200 - val_loss: 0.9038 - val_categorical_accuracy: 0.8005 - 490ms/epoch - 10ms/step
Epoch 264/1500
51/51 - 0s - loss: 0.2345 - categorical_accuracy: 0.9140 - val_loss: 0.8893 - val_categorical_accuracy: 0.8047 - 480ms/epoch - 9ms/step
Epoch 265/1500
51/51 - 0s - loss: 0.2343 - categorical_accuracy: 0.9152 - val_loss: 0.8869 - val_categorical_accuracy: 0.8034 - 484ms/epoch - 9ms/step
Epoch 266/1500
51/51 - 1s - loss: 0.2608 - categorical_accuracy: 0.9049 - val_loss: 0.8890 - val_categorical_accuracy: 0.7923 - 566ms/epoch - 11ms/step
Epoch 267/1500
51/51 - 0s - loss: 0.2181 - categorical_accuracy: 0.9203 - val_loss: 0.9236 - val_categorical_accuracy: 0.8058 - 490ms/epoch - 10ms/step
Epoch 268/1500
51/51 - 1s - loss: 0.2320 - categorical_accuracy: 0.9164 - val_loss: 0.9987 - val_categorical_accuracy: 0.7907 - 521ms/epoch - 10ms/step
Epoch 269/1500
51/51 - 1s - loss: 0.2212 - categorical_accuracy: 0.9194 - val_loss: 0.9279 - val_categorical_accuracy: 0.7782 - 528ms/epoch - 10ms/step
Epoch 270/1500
51/51 - 1s - loss: 0.2408 - categorical_accuracy: 0.9115 - val_loss: 0.9025 - val_categorical_accuracy: 0.8038 - 543ms/epoch - 11ms/step
Epoch 271/1500
51/51 - 0s - loss: 0.2298 - categorical_accuracy: 0.9171 - val_loss: 0.9374 - val_categorical_accuracy: 0.8085 - 499ms/epoch - 10ms/step
Epoch 272/1500
51/51 - 0s - loss: 0.2425 - categorical_accuracy: 0.9119 - val_loss: 0.8851 - val_categorical_accuracy: 0.8078 - 491ms/epoch - 10ms/step
Epoch 273/1500
51/51 - 0s - loss: 0.2190 - categorical_accuracy: 0.9205 - val_loss: 0.9088 - val_categorical_accuracy: 0.7963 - 490ms/epoch - 10ms/step
Epoch 274/1500
51/51 - 1s - loss: 0.2193 - categorical_accuracy: 0.9190 - val_loss: 0.9269 - val_categorical_accuracy: 0.7970 - 526ms/epoch - 10ms/step
Epoch 275/1500
51/51 - 0s - loss: 0.2302 - categorical_accuracy: 0.9153 - val_loss: 0.9624 - val_categorical_accuracy: 0.7842 - 490ms/epoch - 10ms/step
Epoch 276/1500
51/51 - 0s - loss: 0.2303 - categorical_accuracy: 0.9151 - val_loss: 0.9788 - val_categorical_accuracy: 0.7686 - 490ms/epoch - 10ms/step
Epoch 277/1500
51/51 - 0s - loss: 0.2313 - categorical_accuracy: 0.9164 - val_loss: 0.9287 - val_categorical_accuracy: 0.7993 - 490ms/epoch - 10ms/step
Epoch 278/1500
51/51 - 1s - loss: 0.2387 - categorical_accuracy: 0.9135 - val_loss: 0.9477 - val_categorical_accuracy: 0.8071 - 526ms/epoch - 10ms/step
Epoch 279/1500
51/51 - 1s - loss: 0.2110 - categorical_accuracy: 0.9248 - val_loss: 0.9525 - val_categorical_accuracy: 0.7960 - 537ms/epoch - 11ms/step
Epoch 280/1500
51/51 - 1s - loss: 0.2083 - categorical_accuracy: 0.9237 - val_loss: 0.9679 - val_categorical_accuracy: 0.8043 - 554ms/epoch - 11ms/step
Epoch 281/1500
51/51 - 1s - loss: 0.2348 - categorical_accuracy: 0.9132 - val_loss: 1.0047 - val_categorical_accuracy: 0.7792 - 562ms/epoch - 11ms/step
Epoch 282/1500
51/51 - 1s - loss: 0.2375 - categorical_accuracy: 0.9145 - val_loss: 0.9505 - val_categorical_accuracy: 0.8020 - 550ms/epoch - 11ms/step
Epoch 283/1500
51/51 - 0s - loss: 0.2108 - categorical_accuracy: 0.9234 - val_loss: 1.0285 - val_categorical_accuracy: 0.7645 - 487ms/epoch - 10ms/step
Epoch 284/1500
51/51 - 0s - loss: 0.2065 - categorical_accuracy: 0.9257 - val_loss: 1.0752 - val_categorical_accuracy: 0.8074 - 487ms/epoch - 10ms/step
Epoch 285/1500
51/51 - 1s - loss: 0.2448 - categorical_accuracy: 0.9109 - val_loss: 1.0359 - val_categorical_accuracy: 0.7915 - 774ms/epoch - 15ms/step
Epoch 286/1500
51/51 - 1s - loss: 0.2567 - categorical_accuracy: 0.9079 - val_loss: 0.8985 - val_categorical_accuracy: 0.8022 - 559ms/epoch - 11ms/step
Epoch 287/1500
51/51 - 1s - loss: 0.2118 - categorical_accuracy: 0.9218 - val_loss: 1.0383 - val_categorical_accuracy: 0.8036 - 530ms/epoch - 10ms/step
Epoch 288/1500
51/51 - 1s - loss: 0.2056 - categorical_accuracy: 0.9253 - val_loss: 0.9617 - val_categorical_accuracy: 0.7951 - 500ms/epoch - 10ms/step
Epoch 289/1500
51/51 - 1s - loss: 0.2041 - categorical_accuracy: 0.9244 - val_loss: 1.1306 - val_categorical_accuracy: 0.7375 - 501ms/epoch - 10ms/step
Epoch 290/1500
51/51 - 1s - loss: 0.2231 - categorical_accuracy: 0.9198 - val_loss: 0.9582 - val_categorical_accuracy: 0.7954 - 607ms/epoch - 12ms/step
Epoch 291/1500
51/51 - 0s - loss: 0.1942 - categorical_accuracy: 0.9280 - val_loss: 1.0503 - val_categorical_accuracy: 0.7985 - 479ms/epoch - 9ms/step
Epoch 292/1500
51/51 - 0s - loss: 0.1982 - categorical_accuracy: 0.9255 - val_loss: 0.9893 - val_categorical_accuracy: 0.7987 - 461ms/epoch - 9ms/step
Epoch 293/1500
51/51 - 0s - loss: 0.2264 - categorical_accuracy: 0.9171 - val_loss: 0.9719 - val_categorical_accuracy: 0.7751 - 473ms/epoch - 9ms/step
Epoch 294/1500
51/51 - 0s - loss: 0.1984 - categorical_accuracy: 0.9266 - val_loss: 1.0414 - val_categorical_accuracy: 0.7765 - 473ms/epoch - 9ms/step
Epoch 295/1500
51/51 - 0s - loss: 0.2356 - categorical_accuracy: 0.9159 - val_loss: 0.9760 - val_categorical_accuracy: 0.7768 - 494ms/epoch - 10ms/step
Epoch 296/1500
51/51 - 0s - loss: 0.1866 - categorical_accuracy: 0.9324 - val_loss: 0.9989 - val_categorical_accuracy: 0.7985 - 459ms/epoch - 9ms/step
Epoch 297/1500
51/51 - 0s - loss: 0.2290 - categorical_accuracy: 0.9168 - val_loss: 0.9182 - val_categorical_accuracy: 0.7795 - 478ms/epoch - 9ms/step
Epoch 298/1500
51/51 - 0s - loss: 0.2196 - categorical_accuracy: 0.9201 - val_loss: 0.9846 - val_categorical_accuracy: 0.8045 - 459ms/epoch - 9ms/step
Epoch 299/1500
51/51 - 0s - loss: 0.2076 - categorical_accuracy: 0.9246 - val_loss: 1.0133 - val_categorical_accuracy: 0.8013 - 462ms/epoch - 9ms/step
Epoch 300/1500
51/51 - 0s - loss: 0.1842 - categorical_accuracy: 0.9321 - val_loss: 1.0624 - val_categorical_accuracy: 0.8005 - 476ms/epoch - 9ms/step
Epoch 301/1500
51/51 - 0s - loss: 0.2137 - categorical_accuracy: 0.9222 - val_loss: 1.0488 - val_categorical_accuracy: 0.8039 - 446ms/epoch - 9ms/step
Epoch 302/1500
51/51 - 0s - loss: 0.2180 - categorical_accuracy: 0.9224 - val_loss: 1.0133 - val_categorical_accuracy: 0.8012 - 495ms/epoch - 10ms/step
Epoch 303/1500
51/51 - 0s - loss: 0.1920 - categorical_accuracy: 0.9287 - val_loss: 1.0011 - val_categorical_accuracy: 0.7964 - 477ms/epoch - 9ms/step
Epoch 304/1500
51/51 - 0s - loss: 0.2194 - categorical_accuracy: 0.9206 - val_loss: 1.0639 - val_categorical_accuracy: 0.7968 - 474ms/epoch - 9ms/step
Epoch 305/1500
51/51 - 0s - loss: 0.2070 - categorical_accuracy: 0.9227 - val_loss: 1.0562 - val_categorical_accuracy: 0.7961 - 473ms/epoch - 9ms/step
Epoch 306/1500
51/51 - 0s - loss: 0.1918 - categorical_accuracy: 0.9293 - val_loss: 1.4829 - val_categorical_accuracy: 0.7841 - 486ms/epoch - 10ms/step
Epoch 307/1500
51/51 - 0s - loss: 0.2506 - categorical_accuracy: 0.9087 - val_loss: 0.9814 - val_categorical_accuracy: 0.7986 - 464ms/epoch - 9ms/step
Epoch 308/1500
51/51 - 0s - loss: 0.1839 - categorical_accuracy: 0.9322 - val_loss: 1.0779 - val_categorical_accuracy: 0.7429 - 478ms/epoch - 9ms/step
Epoch 309/1500
51/51 - 0s - loss: 0.1908 - categorical_accuracy: 0.9288 - val_loss: 1.0787 - val_categorical_accuracy: 0.7736 - 460ms/epoch - 9ms/step
Epoch 310/1500
51/51 - 1s - loss: 0.1990 - categorical_accuracy: 0.9275 - val_loss: 1.0573 - val_categorical_accuracy: 0.7922 - 509ms/epoch - 10ms/step
Epoch 311/1500
51/51 - 0s - loss: 0.1997 - categorical_accuracy: 0.9264 - val_loss: 1.0359 - val_categorical_accuracy: 0.8023 - 446ms/epoch - 9ms/step
Epoch 312/1500
51/51 - 0s - loss: 0.2121 - categorical_accuracy: 0.9220 - val_loss: 1.1322 - val_categorical_accuracy: 0.7277 - 490ms/epoch - 10ms/step
Epoch 313/1500
51/51 - 0s - loss: 0.1937 - categorical_accuracy: 0.9291 - val_loss: 1.0392 - val_categorical_accuracy: 0.7911 - 456ms/epoch - 9ms/step
Epoch 314/1500
51/51 - 0s - loss: 0.2030 - categorical_accuracy: 0.9247 - val_loss: 1.0690 - val_categorical_accuracy: 0.7675 - 495ms/epoch - 10ms/step
Epoch 315/1500
51/51 - 0s - loss: 0.1985 - categorical_accuracy: 0.9247 - val_loss: 1.1969 - val_categorical_accuracy: 0.7427 - 474ms/epoch - 9ms/step
Epoch 316/1500
51/51 - 1s - loss: 0.2104 - categorical_accuracy: 0.9247 - val_loss: 1.0799 - val_categorical_accuracy: 0.7895 - 523ms/epoch - 10ms/step
Epoch 317/1500
51/51 - 0s - loss: 0.1991 - categorical_accuracy: 0.9288 - val_loss: 1.0329 - val_categorical_accuracy: 0.7945 - 462ms/epoch - 9ms/step
Epoch 318/1500
51/51 - 0s - loss: 0.1982 - categorical_accuracy: 0.9295 - val_loss: 1.0050 - val_categorical_accuracy: 0.7898 - 476ms/epoch - 9ms/step
Epoch 319/1500
51/51 - 0s - loss: 0.1764 - categorical_accuracy: 0.9355 - val_loss: 1.1584 - val_categorical_accuracy: 0.8029 - 476ms/epoch - 9ms/step
Epoch 320/1500
51/51 - 0s - loss: 0.2058 - categorical_accuracy: 0.9258 - val_loss: 1.0744 - val_categorical_accuracy: 0.8033 - 474ms/epoch - 9ms/step
Epoch 321/1500
51/51 - 0s - loss: 0.2436 - categorical_accuracy: 0.9124 - val_loss: 0.9935 - val_categorical_accuracy: 0.7953 - 498ms/epoch - 10ms/step
Epoch 322/1500
51/51 - 0s - loss: 0.1766 - categorical_accuracy: 0.9339 - val_loss: 1.0587 - val_categorical_accuracy: 0.7941 - 476ms/epoch - 9ms/step
Epoch 323/1500
51/51 - 0s - loss: 0.1750 - categorical_accuracy: 0.9363 - val_loss: 1.0715 - val_categorical_accuracy: 0.8025 - 472ms/epoch - 9ms/step
Epoch 324/1500
51/51 - 0s - loss: 0.2196 - categorical_accuracy: 0.9248 - val_loss: 1.1018 - val_categorical_accuracy: 0.7588 - 447ms/epoch - 9ms/step
Epoch 325/1500
51/51 - 0s - loss: 0.1786 - categorical_accuracy: 0.9351 - val_loss: 1.0684 - val_categorical_accuracy: 0.7989 - 479ms/epoch - 9ms/step
Epoch 326/1500
51/51 - 0s - loss: 0.1750 - categorical_accuracy: 0.9344 - val_loss: 1.0833 - val_categorical_accuracy: 0.7921 - 443ms/epoch - 9ms/step
Epoch 327/1500
51/51 - 0s - loss: 0.1779 - categorical_accuracy: 0.9349 - val_loss: 1.1026 - val_categorical_accuracy: 0.8020 - 489ms/epoch - 10ms/step
Epoch 328/1500
51/51 - 0s - loss: 0.1702 - categorical_accuracy: 0.9372 - val_loss: 1.1434 - val_categorical_accuracy: 0.8060 - 445ms/epoch - 9ms/step
Epoch 329/1500
51/51 - 1s - loss: 0.1779 - categorical_accuracy: 0.9354 - val_loss: 1.1420 - val_categorical_accuracy: 0.7974 - 509ms/epoch - 10ms/step
Epoch 330/1500
51/51 - 0s - loss: 0.1679 - categorical_accuracy: 0.9392 - val_loss: 1.2437 - val_categorical_accuracy: 0.7771 - 441ms/epoch - 9ms/step
Epoch 331/1500
51/51 - 0s - loss: 0.2140 - categorical_accuracy: 0.9234 - val_loss: 1.0632 - val_categorical_accuracy: 0.7984 - 493ms/epoch - 10ms/step
Epoch 332/1500
51/51 - 0s - loss: 0.1564 - categorical_accuracy: 0.9428 - val_loss: 1.1174 - val_categorical_accuracy: 0.7974 - 440ms/epoch - 9ms/step
Epoch 333/1500
51/51 - 0s - loss: 0.1910 - categorical_accuracy: 0.9330 - val_loss: 1.0801 - val_categorical_accuracy: 0.7983 - 475ms/epoch - 9ms/step
Epoch 334/1500
51/51 - 0s - loss: 0.1743 - categorical_accuracy: 0.9356 - val_loss: 1.1943 - val_categorical_accuracy: 0.7807 - 458ms/epoch - 9ms/step
Epoch 335/1500
51/51 - 0s - loss: 0.2250 - categorical_accuracy: 0.9207 - val_loss: 1.0549 - val_categorical_accuracy: 0.8018 - 476ms/epoch - 9ms/step
Epoch 336/1500
51/51 - 0s - loss: 0.1670 - categorical_accuracy: 0.9392 - val_loss: 1.1264 - val_categorical_accuracy: 0.8046 - 456ms/epoch - 9ms/step
Epoch 337/1500
51/51 - 0s - loss: 0.1899 - categorical_accuracy: 0.9293 - val_loss: 1.1436 - val_categorical_accuracy: 0.7773 - 459ms/epoch - 9ms/step
Epoch 338/1500
51/51 - 0s - loss: 0.1720 - categorical_accuracy: 0.9356 - val_loss: 1.1365 - val_categorical_accuracy: 0.7988 - 470ms/epoch - 9ms/step
Epoch 339/1500
51/51 - 0s - loss: 0.1740 - categorical_accuracy: 0.9358 - val_loss: 1.3511 - val_categorical_accuracy: 0.8007 - 458ms/epoch - 9ms/step
Epoch 340/1500
51/51 - 0s - loss: 0.1991 - categorical_accuracy: 0.9268 - val_loss: 1.0903 - val_categorical_accuracy: 0.7880 - 477ms/epoch - 9ms/step
Epoch 341/1500
51/51 - 0s - loss: 0.1593 - categorical_accuracy: 0.9401 - val_loss: 1.1294 - val_categorical_accuracy: 0.7912 - 444ms/epoch - 9ms/step
Epoch 342/1500
51/51 - 0s - loss: 0.2180 - categorical_accuracy: 0.9268 - val_loss: 1.0560 - val_categorical_accuracy: 0.7936 - 474ms/epoch - 9ms/step
Epoch 343/1500
51/51 - 0s - loss: 0.1739 - categorical_accuracy: 0.9357 - val_loss: 1.0923 - val_categorical_accuracy: 0.8052 - 458ms/epoch - 9ms/step
Epoch 344/1500
51/51 - 0s - loss: 0.1553 - categorical_accuracy: 0.9428 - val_loss: 1.0962 - val_categorical_accuracy: 0.7950 - 475ms/epoch - 9ms/step
Epoch 345/1500
51/51 - 0s - loss: 0.1716 - categorical_accuracy: 0.9360 - val_loss: 1.1602 - val_categorical_accuracy: 0.7886 - 461ms/epoch - 9ms/step
Epoch 346/1500
51/51 - 0s - loss: 0.1595 - categorical_accuracy: 0.9414 - val_loss: 1.1700 - val_categorical_accuracy: 0.8025 - 482ms/epoch - 9ms/step
Epoch 347/1500
51/51 - 0s - loss: 0.2246 - categorical_accuracy: 0.9229 - val_loss: 1.0609 - val_categorical_accuracy: 0.8063 - 486ms/epoch - 10ms/step
Epoch 348/1500
51/51 - 0s - loss: 0.1582 - categorical_accuracy: 0.9415 - val_loss: 1.1286 - val_categorical_accuracy: 0.7977 - 476ms/epoch - 9ms/step
Epoch 349/1500
51/51 - 0s - loss: 0.1726 - categorical_accuracy: 0.9364 - val_loss: 1.1430 - val_categorical_accuracy: 0.7938 - 458ms/epoch - 9ms/step
Epoch 350/1500
51/51 - 0s - loss: 0.1608 - categorical_accuracy: 0.9409 - val_loss: 1.1433 - val_categorical_accuracy: 0.7968 - 489ms/epoch - 10ms/step
Epoch 351/1500
51/51 - 0s - loss: 0.1789 - categorical_accuracy: 0.9331 - val_loss: 1.2035 - val_categorical_accuracy: 0.8060 - 456ms/epoch - 9ms/step
Epoch 352/1500
51/51 - 0s - loss: 0.1638 - categorical_accuracy: 0.9409 - val_loss: 1.1245 - val_categorical_accuracy: 0.8018 - 489ms/epoch - 10ms/step
Epoch 353/1500
51/51 - 1s - loss: 0.1716 - categorical_accuracy: 0.9371 - val_loss: 2.2977 - val_categorical_accuracy: 0.6375 - 520ms/epoch - 10ms/step
Epoch 354/1500
51/51 - 1s - loss: 0.3105 - categorical_accuracy: 0.9080 - val_loss: 1.0818 - val_categorical_accuracy: 0.8015 - 523ms/epoch - 10ms/step
Epoch 355/1500
51/51 - 1s - loss: 0.1572 - categorical_accuracy: 0.9435 - val_loss: 1.1756 - val_categorical_accuracy: 0.8066 - 524ms/epoch - 10ms/step
Epoch 356/1500
51/51 - 1s - loss: 0.1572 - categorical_accuracy: 0.9434 - val_loss: 1.1753 - val_categorical_accuracy: 0.7916 - 551ms/epoch - 11ms/step
Epoch 357/1500
51/51 - 1s - loss: 0.1497 - categorical_accuracy: 0.9449 - val_loss: 1.1679 - val_categorical_accuracy: 0.8048 - 508ms/epoch - 10ms/step
Epoch 358/1500
51/51 - 1s - loss: 0.1474 - categorical_accuracy: 0.9452 - val_loss: 1.1720 - val_categorical_accuracy: 0.8048 - 533ms/epoch - 10ms/step
Epoch 359/1500
51/51 - 1s - loss: 0.2011 - categorical_accuracy: 0.9305 - val_loss: 1.1837 - val_categorical_accuracy: 0.7865 - 507ms/epoch - 10ms/step
Epoch 360/1500
51/51 - 1s - loss: 0.1584 - categorical_accuracy: 0.9421 - val_loss: 1.1678 - val_categorical_accuracy: 0.8040 - 521ms/epoch - 10ms/step
Epoch 361/1500
51/51 - 1s - loss: 0.1866 - categorical_accuracy: 0.9330 - val_loss: 1.2027 - val_categorical_accuracy: 0.7644 - 504ms/epoch - 10ms/step
Epoch 362/1500
51/51 - 1s - loss: 0.1805 - categorical_accuracy: 0.9331 - val_loss: 1.8213 - val_categorical_accuracy: 0.7798 - 526ms/epoch - 10ms/step
Epoch 363/1500
51/51 - 0s - loss: 0.2023 - categorical_accuracy: 0.9291 - val_loss: 1.1614 - val_categorical_accuracy: 0.7821 - 488ms/epoch - 10ms/step
Epoch 364/1500
51/51 - 1s - loss: 0.1493 - categorical_accuracy: 0.9449 - val_loss: 1.1719 - val_categorical_accuracy: 0.7919 - 536ms/epoch - 11ms/step
Epoch 365/1500
51/51 - 0s - loss: 0.1561 - categorical_accuracy: 0.9418 - val_loss: 1.2261 - val_categorical_accuracy: 0.8066 - 494ms/epoch - 10ms/step
Epoch 366/1500
51/51 - 1s - loss: 0.1707 - categorical_accuracy: 0.9358 - val_loss: 1.2115 - val_categorical_accuracy: 0.7982 - 537ms/epoch - 11ms/step
Epoch 367/1500
51/51 - 1s - loss: 0.1775 - categorical_accuracy: 0.9344 - val_loss: 1.1406 - val_categorical_accuracy: 0.7952 - 500ms/epoch - 10ms/step
Epoch 368/1500
51/51 - 1s - loss: 0.1544 - categorical_accuracy: 0.9445 - val_loss: 1.3168 - val_categorical_accuracy: 0.7680 - 524ms/epoch - 10ms/step
Epoch 369/1500
51/51 - 0s - loss: 0.1779 - categorical_accuracy: 0.9341 - val_loss: 1.3850 - val_categorical_accuracy: 0.7893 - 486ms/epoch - 10ms/step
Epoch 370/1500
51/51 - 1s - loss: 0.1778 - categorical_accuracy: 0.9345 - val_loss: 1.1471 - val_categorical_accuracy: 0.7979 - 526ms/epoch - 10ms/step
Epoch 371/1500
51/51 - 1s - loss: 0.1611 - categorical_accuracy: 0.9409 - val_loss: 1.1529 - val_categorical_accuracy: 0.7849 - 510ms/epoch - 10ms/step
Epoch 372/1500
51/51 - 1s - loss: 0.1838 - categorical_accuracy: 0.9396 - val_loss: 1.4284 - val_categorical_accuracy: 0.7808 - 525ms/epoch - 10ms/step
Epoch 373/1500
51/51 - 1s - loss: 0.1762 - categorical_accuracy: 0.9373 - val_loss: 1.1505 - val_categorical_accuracy: 0.8100 - 508ms/epoch - 10ms/step
Epoch 374/1500
51/51 - 1s - loss: 0.1526 - categorical_accuracy: 0.9437 - val_loss: 1.1811 - val_categorical_accuracy: 0.8037 - 508ms/epoch - 10ms/step
Epoch 375/1500
51/51 - 1s - loss: 0.1883 - categorical_accuracy: 0.9334 - val_loss: 1.1004 - val_categorical_accuracy: 0.7941 - 504ms/epoch - 10ms/step
Epoch 376/1500
51/51 - 1s - loss: 0.1514 - categorical_accuracy: 0.9430 - val_loss: 1.2922 - val_categorical_accuracy: 0.8044 - 511ms/epoch - 10ms/step
Epoch 377/1500
51/51 - 1s - loss: 0.1577 - categorical_accuracy: 0.9412 - val_loss: 1.2303 - val_categorical_accuracy: 0.8038 - 524ms/epoch - 10ms/step
Epoch 378/1500
51/51 - 1s - loss: 0.1610 - categorical_accuracy: 0.9403 - val_loss: 1.2319 - val_categorical_accuracy: 0.7991 - 512ms/epoch - 10ms/step
Epoch 379/1500
51/51 - 1s - loss: 0.1504 - categorical_accuracy: 0.9447 - val_loss: 1.2205 - val_categorical_accuracy: 0.7974 - 511ms/epoch - 10ms/step
Epoch 380/1500
51/51 - 1s - loss: 0.2473 - categorical_accuracy: 0.9213 - val_loss: 1.1355 - val_categorical_accuracy: 0.7914 - 504ms/epoch - 10ms/step
Epoch 381/1500
51/51 - 1s - loss: 0.1402 - categorical_accuracy: 0.9491 - val_loss: 1.1804 - val_categorical_accuracy: 0.8030 - 508ms/epoch - 10ms/step
Epoch 382/1500
51/51 - 1s - loss: 0.1406 - categorical_accuracy: 0.9477 - val_loss: 1.2249 - val_categorical_accuracy: 0.7992 - 510ms/epoch - 10ms/step
Epoch 383/1500
51/51 - 1s - loss: 0.1395 - categorical_accuracy: 0.9475 - val_loss: 1.2534 - val_categorical_accuracy: 0.7954 - 537ms/epoch - 11ms/step
Epoch 384/1500
51/51 - 1s - loss: 0.1499 - categorical_accuracy: 0.9445 - val_loss: 1.2252 - val_categorical_accuracy: 0.7975 - 553ms/epoch - 11ms/step
Epoch 385/1500
51/51 - 1s - loss: 0.1443 - categorical_accuracy: 0.9465 - val_loss: 1.2544 - val_categorical_accuracy: 0.7938 - 560ms/epoch - 11ms/step
Epoch 386/1500
51/51 - 1s - loss: 0.1427 - categorical_accuracy: 0.9464 - val_loss: 1.2656 - val_categorical_accuracy: 0.7964 - 556ms/epoch - 11ms/step
Epoch 387/1500
51/51 - 1s - loss: 0.1559 - categorical_accuracy: 0.9423 - val_loss: 1.2516 - val_categorical_accuracy: 0.7931 - 539ms/epoch - 11ms/step
Epoch 388/1500
51/51 - 1s - loss: 0.1400 - categorical_accuracy: 0.9486 - val_loss: 1.2633 - val_categorical_accuracy: 0.7829 - 523ms/epoch - 10ms/step
Epoch 389/1500
51/51 - 1s - loss: 0.2063 - categorical_accuracy: 0.9309 - val_loss: 1.1265 - val_categorical_accuracy: 0.7911 - 571ms/epoch - 11ms/step
Epoch 390/1500
51/51 - 1s - loss: 0.1465 - categorical_accuracy: 0.9451 - val_loss: 1.2772 - val_categorical_accuracy: 0.7865 - 540ms/epoch - 11ms/step
Epoch 391/1500
51/51 - 1s - loss: 0.1512 - categorical_accuracy: 0.9442 - val_loss: 1.2196 - val_categorical_accuracy: 0.7962 - 541ms/epoch - 11ms/step
Epoch 392/1500
51/51 - 1s - loss: 0.1433 - categorical_accuracy: 0.9476 - val_loss: 1.3432 - val_categorical_accuracy: 0.8031 - 526ms/epoch - 10ms/step
Epoch 393/1500
51/51 - 0s - loss: 0.2086 - categorical_accuracy: 0.9243 - val_loss: 1.1675 - val_categorical_accuracy: 0.7892 - 490ms/epoch - 10ms/step
Epoch 394/1500
51/51 - 1s - loss: 0.1409 - categorical_accuracy: 0.9482 - val_loss: 1.2604 - val_categorical_accuracy: 0.7896 - 539ms/epoch - 11ms/step
Epoch 395/1500
51/51 - 1s - loss: 0.2000 - categorical_accuracy: 0.9319 - val_loss: 1.1998 - val_categorical_accuracy: 0.7757 - 510ms/epoch - 10ms/step
Epoch 396/1500
51/51 - 1s - loss: 0.1479 - categorical_accuracy: 0.9456 - val_loss: 1.2388 - val_categorical_accuracy: 0.8032 - 526ms/epoch - 10ms/step
Epoch 397/1500
51/51 - 1s - loss: 0.1365 - categorical_accuracy: 0.9493 - val_loss: 1.2736 - val_categorical_accuracy: 0.8045 - 510ms/epoch - 10ms/step
Epoch 398/1500
51/51 - 1s - loss: 0.1356 - categorical_accuracy: 0.9506 - val_loss: 1.2637 - val_categorical_accuracy: 0.8024 - 524ms/epoch - 10ms/step
Epoch 399/1500
51/51 - 0s - loss: 0.1374 - categorical_accuracy: 0.9488 - val_loss: 1.3133 - val_categorical_accuracy: 0.8054 - 491ms/epoch - 10ms/step
Epoch 400/1500
51/51 - 1s - loss: 0.1385 - categorical_accuracy: 0.9482 - val_loss: 1.2818 - val_categorical_accuracy: 0.7910 - 540ms/epoch - 11ms/step
Epoch 401/1500
51/51 - 1s - loss: 0.1333 - categorical_accuracy: 0.9507 - val_loss: 1.3850 - val_categorical_accuracy: 0.7727 - 504ms/epoch - 10ms/step
Epoch 402/1500
51/51 - 1s - loss: 0.1540 - categorical_accuracy: 0.9419 - val_loss: 1.3113 - val_categorical_accuracy: 0.7938 - 541ms/epoch - 11ms/step
Epoch 403/1500
51/51 - 0s - loss: 0.2711 - categorical_accuracy: 0.9119 - val_loss: 1.1919 - val_categorical_accuracy: 0.8030 - 490ms/epoch - 10ms/step
Epoch 404/1500
51/51 - 1s - loss: 0.1373 - categorical_accuracy: 0.9487 - val_loss: 1.2295 - val_categorical_accuracy: 0.7995 - 545ms/epoch - 11ms/step
Epoch 405/1500
51/51 - 1s - loss: 0.1368 - categorical_accuracy: 0.9501 - val_loss: 1.3800 - val_categorical_accuracy: 0.7900 - 505ms/epoch - 10ms/step
Epoch 406/1500
51/51 - 1s - loss: 0.1491 - categorical_accuracy: 0.9445 - val_loss: 1.2425 - val_categorical_accuracy: 0.7938 - 521ms/epoch - 10ms/step
Epoch 407/1500
51/51 - 0s - loss: 0.1283 - categorical_accuracy: 0.9529 - val_loss: 1.3346 - val_categorical_accuracy: 0.8024 - 493ms/epoch - 10ms/step
Epoch 408/1500
51/51 - 1s - loss: 0.1445 - categorical_accuracy: 0.9455 - val_loss: 1.3534 - val_categorical_accuracy: 0.7956 - 522ms/epoch - 10ms/step
Epoch 409/1500
51/51 - 0s - loss: 0.1439 - categorical_accuracy: 0.9456 - val_loss: 1.3253 - val_categorical_accuracy: 0.7826 - 494ms/epoch - 10ms/step
Epoch 410/1500
51/51 - 1s - loss: 0.2451 - categorical_accuracy: 0.9160 - val_loss: 1.2038 - val_categorical_accuracy: 0.7991 - 521ms/epoch - 10ms/step
Epoch 411/1500
51/51 - 0s - loss: 0.1343 - categorical_accuracy: 0.9502 - val_loss: 1.3260 - val_categorical_accuracy: 0.7944 - 477ms/epoch - 9ms/step
Epoch 412/1500
51/51 - 1s - loss: 0.1439 - categorical_accuracy: 0.9451 - val_loss: 1.3183 - val_categorical_accuracy: 0.7998 - 521ms/epoch - 10ms/step
Epoch 413/1500
51/51 - 1s - loss: 0.1441 - categorical_accuracy: 0.9467 - val_loss: 1.3077 - val_categorical_accuracy: 0.7927 - 516ms/epoch - 10ms/step
Epoch 414/1500
51/51 - 1s - loss: 0.2202 - categorical_accuracy: 0.9282 - val_loss: 1.1853 - val_categorical_accuracy: 0.8033 - 518ms/epoch - 10ms/step
Epoch 415/1500
51/51 - 1s - loss: 0.1309 - categorical_accuracy: 0.9518 - val_loss: 1.2633 - val_categorical_accuracy: 0.7952 - 506ms/epoch - 10ms/step
Epoch 416/1500
51/51 - 1s - loss: 0.1350 - categorical_accuracy: 0.9501 - val_loss: 1.3149 - val_categorical_accuracy: 0.7988 - 529ms/epoch - 10ms/step
Epoch 417/1500
51/51 - 0s - loss: 0.1358 - categorical_accuracy: 0.9498 - val_loss: 1.3444 - val_categorical_accuracy: 0.8053 - 488ms/epoch - 10ms/step
Epoch 418/1500
51/51 - 1s - loss: 0.1673 - categorical_accuracy: 0.9394 - val_loss: 1.2413 - val_categorical_accuracy: 0.7897 - 517ms/epoch - 10ms/step
Epoch 419/1500
51/51 - 1s - loss: 0.1469 - categorical_accuracy: 0.9449 - val_loss: 1.3387 - val_categorical_accuracy: 0.8037 - 503ms/epoch - 10ms/step
Epoch 420/1500
51/51 - 1s - loss: 0.1276 - categorical_accuracy: 0.9522 - val_loss: 1.3370 - val_categorical_accuracy: 0.8076 - 504ms/epoch - 10ms/step
Epoch 421/1500
51/51 - 1s - loss: 0.1389 - categorical_accuracy: 0.9474 - val_loss: 1.3696 - val_categorical_accuracy: 0.7749 - 518ms/epoch - 10ms/step
Epoch 422/1500
51/51 - 1s - loss: 0.1820 - categorical_accuracy: 0.9368 - val_loss: 1.1872 - val_categorical_accuracy: 0.7915 - 500ms/epoch - 10ms/step
Epoch 423/1500
51/51 - 0s - loss: 0.1440 - categorical_accuracy: 0.9455 - val_loss: 1.2726 - val_categorical_accuracy: 0.7921 - 496ms/epoch - 10ms/step
Epoch 424/1500
51/51 - 1s - loss: 0.1320 - categorical_accuracy: 0.9498 - val_loss: 1.3273 - val_categorical_accuracy: 0.7833 - 527ms/epoch - 10ms/step
Epoch 425/1500
51/51 - 1s - loss: 0.1277 - categorical_accuracy: 0.9523 - val_loss: 1.3996 - val_categorical_accuracy: 0.7976 - 517ms/epoch - 10ms/step
Epoch 426/1500
51/51 - 1s - loss: 0.2873 - categorical_accuracy: 0.9090 - val_loss: 1.1943 - val_categorical_accuracy: 0.8045 - 502ms/epoch - 10ms/step
Epoch 427/1500
51/51 - 1s - loss: 0.1292 - categorical_accuracy: 0.9512 - val_loss: 1.2637 - val_categorical_accuracy: 0.7963 - 518ms/epoch - 10ms/step
Epoch 428/1500
51/51 - 1s - loss: 0.1245 - categorical_accuracy: 0.9541 - val_loss: 1.3003 - val_categorical_accuracy: 0.8046 - 507ms/epoch - 10ms/step
Epoch 429/1500
51/51 - 1s - loss: 0.1247 - categorical_accuracy: 0.9533 - val_loss: 1.3164 - val_categorical_accuracy: 0.8063 - 503ms/epoch - 10ms/step
Epoch 430/1500
51/51 - 1s - loss: 0.1215 - categorical_accuracy: 0.9556 - val_loss: 1.3727 - val_categorical_accuracy: 0.8062 - 510ms/epoch - 10ms/step
Epoch 431/1500
51/51 - 1s - loss: 0.1248 - categorical_accuracy: 0.9528 - val_loss: 1.3974 - val_categorical_accuracy: 0.8083 - 524ms/epoch - 10ms/step
Epoch 432/1500
51/51 - 1s - loss: 0.1903 - categorical_accuracy: 0.9334 - val_loss: 1.2889 - val_categorical_accuracy: 0.7890 - 504ms/epoch - 10ms/step
Epoch 433/1500
51/51 - 1s - loss: 0.1321 - categorical_accuracy: 0.9505 - val_loss: 1.3207 - val_categorical_accuracy: 0.7915 - 523ms/epoch - 10ms/step
Epoch 434/1500
51/51 - 1s - loss: 0.2048 - categorical_accuracy: 0.9287 - val_loss: 1.2312 - val_categorical_accuracy: 0.8031 - 504ms/epoch - 10ms/step
Epoch 435/1500
51/51 - 1s - loss: 0.1305 - categorical_accuracy: 0.9505 - val_loss: 1.3780 - val_categorical_accuracy: 0.8020 - 514ms/epoch - 10ms/step
Epoch 436/1500
51/51 - 0s - loss: 0.1266 - categorical_accuracy: 0.9522 - val_loss: 1.3354 - val_categorical_accuracy: 0.7998 - 494ms/epoch - 10ms/step
Epoch 437/1500
51/51 - 1s - loss: 0.1264 - categorical_accuracy: 0.9525 - val_loss: 1.3776 - val_categorical_accuracy: 0.8003 - 521ms/epoch - 10ms/step
Epoch 438/1500
51/51 - 1s - loss: 0.1333 - categorical_accuracy: 0.9508 - val_loss: 1.3766 - val_categorical_accuracy: 0.7910 - 505ms/epoch - 10ms/step
Epoch 439/1500
51/51 - 1s - loss: 0.1267 - categorical_accuracy: 0.9525 - val_loss: 1.3764 - val_categorical_accuracy: 0.8035 - 530ms/epoch - 10ms/step
Epoch 440/1500
51/51 - 1s - loss: 0.1318 - categorical_accuracy: 0.9506 - val_loss: 1.4358 - val_categorical_accuracy: 0.7947 - 506ms/epoch - 10ms/step
Epoch 441/1500
51/51 - 1s - loss: 0.1288 - categorical_accuracy: 0.9520 - val_loss: 1.3858 - val_categorical_accuracy: 0.7966 - 522ms/epoch - 10ms/step
Epoch 442/1500
51/51 - 0s - loss: 0.1264 - categorical_accuracy: 0.9529 - val_loss: 1.3902 - val_categorical_accuracy: 0.7980 - 479ms/epoch - 9ms/step
Epoch 443/1500
51/51 - 1s - loss: 0.1371 - categorical_accuracy: 0.9486 - val_loss: 1.3844 - val_categorical_accuracy: 0.7997 - 506ms/epoch - 10ms/step
Epoch 444/1500
51/51 - 1s - loss: 0.1263 - categorical_accuracy: 0.9533 - val_loss: 1.4679 - val_categorical_accuracy: 0.8057 - 516ms/epoch - 10ms/step
Epoch 445/1500
51/51 - 1s - loss: 0.2175 - categorical_accuracy: 0.9262 - val_loss: 1.2034 - val_categorical_accuracy: 0.7850 - 519ms/epoch - 10ms/step
Epoch 446/1500
51/51 - 0s - loss: 0.1340 - categorical_accuracy: 0.9489 - val_loss: 1.3275 - val_categorical_accuracy: 0.8017 - 496ms/epoch - 10ms/step
Epoch 447/1500
51/51 - 1s - loss: 0.1379 - categorical_accuracy: 0.9496 - val_loss: 1.3743 - val_categorical_accuracy: 0.7712 - 524ms/epoch - 10ms/step
Epoch 448/1500
51/51 - 0s - loss: 0.1496 - categorical_accuracy: 0.9450 - val_loss: 1.3336 - val_categorical_accuracy: 0.8058 - 473ms/epoch - 9ms/step
Epoch 449/1500
51/51 - 1s - loss: 0.1202 - categorical_accuracy: 0.9556 - val_loss: 1.4103 - val_categorical_accuracy: 0.7991 - 515ms/epoch - 10ms/step
Epoch 450/1500
51/51 - 0s - loss: 0.1338 - categorical_accuracy: 0.9508 - val_loss: 1.4206 - val_categorical_accuracy: 0.7684 - 487ms/epoch - 10ms/step
Epoch 451/1500
51/51 - 1s - loss: 0.1661 - categorical_accuracy: 0.9393 - val_loss: 1.3142 - val_categorical_accuracy: 0.7980 - 534ms/epoch - 10ms/step
Epoch 452/1500
51/51 - 0s - loss: 0.1263 - categorical_accuracy: 0.9521 - val_loss: 1.3711 - val_categorical_accuracy: 0.7923 - 495ms/epoch - 10ms/step
Epoch 453/1500
51/51 - 1s - loss: 0.1265 - categorical_accuracy: 0.9533 - val_loss: 1.3613 - val_categorical_accuracy: 0.7982 - 527ms/epoch - 10ms/step
Epoch 454/1500
51/51 - 0s - loss: 0.1344 - categorical_accuracy: 0.9491 - val_loss: 1.3641 - val_categorical_accuracy: 0.7858 - 473ms/epoch - 9ms/step
Epoch 455/1500
51/51 - 1s - loss: 0.1238 - categorical_accuracy: 0.9546 - val_loss: 1.3963 - val_categorical_accuracy: 0.8026 - 520ms/epoch - 10ms/step
Epoch 456/1500
51/51 - 0s - loss: 0.1350 - categorical_accuracy: 0.9492 - val_loss: 1.3938 - val_categorical_accuracy: 0.7860 - 495ms/epoch - 10ms/step
Epoch 457/1500
51/51 - 1s - loss: 0.1202 - categorical_accuracy: 0.9552 - val_loss: 1.4105 - val_categorical_accuracy: 0.7758 - 513ms/epoch - 10ms/step
Epoch 458/1500
51/51 - 0s - loss: 0.1230 - categorical_accuracy: 0.9541 - val_loss: 1.4545 - val_categorical_accuracy: 0.7863 - 494ms/epoch - 10ms/step
Epoch 459/1500
51/51 - 1s - loss: 0.2468 - categorical_accuracy: 0.9232 - val_loss: 1.2355 - val_categorical_accuracy: 0.7969 - 525ms/epoch - 10ms/step
Epoch 460/1500
51/51 - 0s - loss: 0.1234 - categorical_accuracy: 0.9543 - val_loss: 1.3667 - val_categorical_accuracy: 0.7909 - 477ms/epoch - 9ms/step
Epoch 461/1500
51/51 - 1s - loss: 0.1174 - categorical_accuracy: 0.9565 - val_loss: 1.3795 - val_categorical_accuracy: 0.7989 - 522ms/epoch - 10ms/step
Epoch 462/1500
51/51 - 0s - loss: 0.1181 - categorical_accuracy: 0.9558 - val_loss: 1.4387 - val_categorical_accuracy: 0.8021 - 497ms/epoch - 10ms/step
Epoch 463/1500
51/51 - 1s - loss: 0.1179 - categorical_accuracy: 0.9551 - val_loss: 1.4284 - val_categorical_accuracy: 0.8059 - 564ms/epoch - 11ms/step
Epoch 464/1500
51/51 - 1s - loss: 0.1167 - categorical_accuracy: 0.9556 - val_loss: 1.4367 - val_categorical_accuracy: 0.7982 - 505ms/epoch - 10ms/step
Epoch 465/1500
51/51 - 1s - loss: 0.1217 - categorical_accuracy: 0.9547 - val_loss: 1.4347 - val_categorical_accuracy: 0.7889 - 511ms/epoch - 10ms/step
Epoch 466/1500
51/51 - 0s - loss: 0.1186 - categorical_accuracy: 0.9554 - val_loss: 1.4906 - val_categorical_accuracy: 0.7743 - 499ms/epoch - 10ms/step
Epoch 467/1500
51/51 - 1s - loss: 0.2140 - categorical_accuracy: 0.9287 - val_loss: 1.3828 - val_categorical_accuracy: 0.8017 - 504ms/epoch - 10ms/step
Epoch 468/1500
51/51 - 1s - loss: 0.1689 - categorical_accuracy: 0.9428 - val_loss: 1.3439 - val_categorical_accuracy: 0.7963 - 522ms/epoch - 10ms/step
Epoch 469/1500
51/51 - 1s - loss: 0.1373 - categorical_accuracy: 0.9481 - val_loss: 1.3877 - val_categorical_accuracy: 0.7999 - 526ms/epoch - 10ms/step
Epoch 470/1500
51/51 - 1s - loss: 0.1192 - categorical_accuracy: 0.9560 - val_loss: 1.4462 - val_categorical_accuracy: 0.7935 - 522ms/epoch - 10ms/step
Epoch 471/1500
51/51 - 1s - loss: 0.1288 - categorical_accuracy: 0.9509 - val_loss: 1.4275 - val_categorical_accuracy: 0.7987 - 523ms/epoch - 10ms/step
Epoch 472/1500
51/51 - 1s - loss: 0.1191 - categorical_accuracy: 0.9537 - val_loss: 1.4207 - val_categorical_accuracy: 0.7991 - 516ms/epoch - 10ms/step
Epoch 473/1500
51/51 - 0s - loss: 0.1229 - categorical_accuracy: 0.9543 - val_loss: 1.3889 - val_categorical_accuracy: 0.7967 - 495ms/epoch - 10ms/step
Epoch 474/1500
51/51 - 1s - loss: 0.1168 - categorical_accuracy: 0.9564 - val_loss: 1.4135 - val_categorical_accuracy: 0.8020 - 523ms/epoch - 10ms/step
Epoch 475/1500
51/51 - 1s - loss: 0.1970 - categorical_accuracy: 0.9397 - val_loss: 1.2999 - val_categorical_accuracy: 0.7740 - 503ms/epoch - 10ms/step
Epoch 476/1500
51/51 - 1s - loss: 0.1534 - categorical_accuracy: 0.9430 - val_loss: 1.3544 - val_categorical_accuracy: 0.7956 - 509ms/epoch - 10ms/step
Epoch 477/1500
51/51 - 0s - loss: 0.1221 - categorical_accuracy: 0.9552 - val_loss: 1.3539 - val_categorical_accuracy: 0.7983 - 488ms/epoch - 10ms/step
Epoch 478/1500
51/51 - 0s - loss: 0.1163 - categorical_accuracy: 0.9563 - val_loss: 1.4562 - val_categorical_accuracy: 0.7898 - 492ms/epoch - 10ms/step
Epoch 479/1500
51/51 - 0s - loss: 0.1189 - categorical_accuracy: 0.9552 - val_loss: 1.4657 - val_categorical_accuracy: 0.7958 - 498ms/epoch - 10ms/step
Epoch 480/1500
51/51 - 1s - loss: 0.2075 - categorical_accuracy: 0.9336 - val_loss: 1.4003 - val_categorical_accuracy: 0.8035 - 517ms/epoch - 10ms/step
Epoch 481/1500
51/51 - 0s - loss: 0.1209 - categorical_accuracy: 0.9541 - val_loss: 1.4115 - val_categorical_accuracy: 0.8071 - 495ms/epoch - 10ms/step
Epoch 482/1500
51/51 - 1s - loss: 0.1108 - categorical_accuracy: 0.9592 - val_loss: 1.4517 - val_categorical_accuracy: 0.7962 - 526ms/epoch - 10ms/step
Epoch 483/1500
51/51 - 1s - loss: 0.1108 - categorical_accuracy: 0.9580 - val_loss: 1.4446 - val_categorical_accuracy: 0.7923 - 540ms/epoch - 11ms/step
Epoch 484/1500
51/51 - 1s - loss: 0.1764 - categorical_accuracy: 0.9432 - val_loss: 1.4685 - val_categorical_accuracy: 0.6790 - 509ms/epoch - 10ms/step
Epoch 485/1500
51/51 - 0s - loss: 0.1491 - categorical_accuracy: 0.9442 - val_loss: 1.3428 - val_categorical_accuracy: 0.8008 - 491ms/epoch - 10ms/step
Epoch 486/1500
51/51 - 1s - loss: 0.1124 - categorical_accuracy: 0.9578 - val_loss: 1.3821 - val_categorical_accuracy: 0.7854 - 523ms/epoch - 10ms/step
Epoch 487/1500
51/51 - 0s - loss: 0.1102 - categorical_accuracy: 0.9570 - val_loss: 1.4832 - val_categorical_accuracy: 0.7890 - 488ms/epoch - 10ms/step
Epoch 488/1500
51/51 - 1s - loss: 0.1136 - categorical_accuracy: 0.9580 - val_loss: 1.4297 - val_categorical_accuracy: 0.7979 - 520ms/epoch - 10ms/step
Epoch 489/1500
51/51 - 0s - loss: 0.1183 - categorical_accuracy: 0.9545 - val_loss: 1.5339 - val_categorical_accuracy: 0.7992 - 490ms/epoch - 10ms/step
Epoch 490/1500
51/51 - 1s - loss: 0.1158 - categorical_accuracy: 0.9569 - val_loss: 1.5584 - val_categorical_accuracy: 0.7940 - 514ms/epoch - 10ms/step
Epoch 491/1500
51/51 - 0s - loss: 0.1528 - categorical_accuracy: 0.9430 - val_loss: 1.4694 - val_categorical_accuracy: 0.7895 - 492ms/epoch - 10ms/step
Epoch 492/1500
51/51 - 1s - loss: 0.1218 - categorical_accuracy: 0.9537 - val_loss: 1.4880 - val_categorical_accuracy: 0.8018 - 527ms/epoch - 10ms/step
Epoch 493/1500
51/51 - 0s - loss: 0.1155 - categorical_accuracy: 0.9556 - val_loss: 1.4869 - val_categorical_accuracy: 0.7837 - 489ms/epoch - 10ms/step
Epoch 494/1500
51/51 - 1s - loss: 0.1416 - categorical_accuracy: 0.9481 - val_loss: 1.3870 - val_categorical_accuracy: 0.7956 - 519ms/epoch - 10ms/step
Epoch 495/1500
51/51 - 1s - loss: 0.1191 - categorical_accuracy: 0.9554 - val_loss: 1.4855 - val_categorical_accuracy: 0.7949 - 501ms/epoch - 10ms/step
Epoch 496/1500
51/51 - 1s - loss: 0.1163 - categorical_accuracy: 0.9549 - val_loss: 1.5217 - val_categorical_accuracy: 0.7953 - 519ms/epoch - 10ms/step
Epoch 497/1500
51/51 - 0s - loss: 0.1111 - categorical_accuracy: 0.9579 - val_loss: 1.5681 - val_categorical_accuracy: 0.7987 - 476ms/epoch - 9ms/step
Epoch 498/1500
51/51 - 1s - loss: 0.1167 - categorical_accuracy: 0.9552 - val_loss: 1.5818 - val_categorical_accuracy: 0.8069 - 532ms/epoch - 10ms/step
Epoch 499/1500
51/51 - 0s - loss: 0.1133 - categorical_accuracy: 0.9564 - val_loss: 1.4977 - val_categorical_accuracy: 0.7865 - 491ms/epoch - 10ms/step
Epoch 500/1500
51/51 - 1s - loss: 0.1207 - categorical_accuracy: 0.9549 - val_loss: 1.5101 - val_categorical_accuracy: 0.7657 - 521ms/epoch - 10ms/step
Epoch 501/1500
51/51 - 0s - loss: 0.1870 - categorical_accuracy: 0.9349 - val_loss: 1.5976 - val_categorical_accuracy: 0.7731 - 490ms/epoch - 10ms/step
Epoch 502/1500
51/51 - 1s - loss: 0.1425 - categorical_accuracy: 0.9475 - val_loss: 1.5516 - val_categorical_accuracy: 0.8023 - 548ms/epoch - 11ms/step
Epoch 503/1500
51/51 - 1s - loss: 0.1980 - categorical_accuracy: 0.9321 - val_loss: 1.4560 - val_categorical_accuracy: 0.8010 - 514ms/epoch - 10ms/step
Epoch 504/1500
51/51 - 1s - loss: 0.1195 - categorical_accuracy: 0.9544 - val_loss: 1.4358 - val_categorical_accuracy: 0.7885 - 559ms/epoch - 11ms/step
Epoch 505/1500
51/51 - 1s - loss: 0.1140 - categorical_accuracy: 0.9567 - val_loss: 1.4472 - val_categorical_accuracy: 0.8054 - 542ms/epoch - 11ms/step
Epoch 506/1500
51/51 - 1s - loss: 0.1085 - categorical_accuracy: 0.9587 - val_loss: 1.5028 - val_categorical_accuracy: 0.7930 - 540ms/epoch - 11ms/step
Epoch 507/1500
51/51 - 1s - loss: 0.1204 - categorical_accuracy: 0.9552 - val_loss: 1.5610 - val_categorical_accuracy: 0.7960 - 568ms/epoch - 11ms/step
Epoch 508/1500
51/51 - 1s - loss: 0.1628 - categorical_accuracy: 0.9428 - val_loss: 1.4860 - val_categorical_accuracy: 0.7733 - 522ms/epoch - 10ms/step
Epoch 509/1500
51/51 - 1s - loss: 0.1092 - categorical_accuracy: 0.9580 - val_loss: 1.4976 - val_categorical_accuracy: 0.8041 - 508ms/epoch - 10ms/step
Epoch 510/1500
51/51 - 0s - loss: 0.1094 - categorical_accuracy: 0.9586 - val_loss: 1.5735 - val_categorical_accuracy: 0.7856 - 486ms/epoch - 10ms/step
Epoch 511/1500
51/51 - 1s - loss: 0.1153 - categorical_accuracy: 0.9568 - val_loss: 1.5379 - val_categorical_accuracy: 0.7879 - 512ms/epoch - 10ms/step
Epoch 512/1500
51/51 - 0s - loss: 0.1106 - categorical_accuracy: 0.9568 - val_loss: 1.4904 - val_categorical_accuracy: 0.7904 - 497ms/epoch - 10ms/step
Epoch 513/1500
51/51 - 1s - loss: 0.1094 - categorical_accuracy: 0.9582 - val_loss: 1.5454 - val_categorical_accuracy: 0.8022 - 536ms/epoch - 11ms/step
Epoch 514/1500
51/51 - 0s - loss: 0.1097 - categorical_accuracy: 0.9585 - val_loss: 1.5837 - val_categorical_accuracy: 0.7924 - 487ms/epoch - 10ms/step
Epoch 515/1500
51/51 - 1s - loss: 0.1217 - categorical_accuracy: 0.9548 - val_loss: 1.8757 - val_categorical_accuracy: 0.7863 - 505ms/epoch - 10ms/step
Epoch 516/1500
51/51 - 0s - loss: 0.2429 - categorical_accuracy: 0.9237 - val_loss: 1.3397 - val_categorical_accuracy: 0.7935 - 490ms/epoch - 10ms/step
Epoch 517/1500
51/51 - 1s - loss: 0.1140 - categorical_accuracy: 0.9575 - val_loss: 1.4581 - val_categorical_accuracy: 0.7879 - 519ms/epoch - 10ms/step
Epoch 518/1500
51/51 - 0s - loss: 0.1179 - categorical_accuracy: 0.9570 - val_loss: 1.4787 - val_categorical_accuracy: 0.7962 - 493ms/epoch - 10ms/step
Epoch 519/1500
51/51 - 1s - loss: 0.1083 - categorical_accuracy: 0.9588 - val_loss: 1.4922 - val_categorical_accuracy: 0.7969 - 520ms/epoch - 10ms/step
Epoch 520/1500
51/51 - 0s - loss: 0.1069 - categorical_accuracy: 0.9598 - val_loss: 1.5089 - val_categorical_accuracy: 0.7998 - 487ms/epoch - 10ms/step
Epoch 521/1500
51/51 - 1s - loss: 0.1091 - categorical_accuracy: 0.9602 - val_loss: 1.5316 - val_categorical_accuracy: 0.8042 - 520ms/epoch - 10ms/step
Epoch 522/1500
51/51 - 1s - loss: 0.1067 - categorical_accuracy: 0.9588 - val_loss: 1.5430 - val_categorical_accuracy: 0.7987 - 500ms/epoch - 10ms/step
Epoch 523/1500
51/51 - 1s - loss: 0.1054 - categorical_accuracy: 0.9595 - val_loss: 1.5699 - val_categorical_accuracy: 0.7984 - 522ms/epoch - 10ms/step
Epoch 524/1500
51/51 - 0s - loss: 0.1315 - categorical_accuracy: 0.9508 - val_loss: 1.5126 - val_categorical_accuracy: 0.7988 - 478ms/epoch - 9ms/step
Epoch 525/1500
51/51 - 1s - loss: 0.1092 - categorical_accuracy: 0.9594 - val_loss: 1.5403 - val_categorical_accuracy: 0.7926 - 536ms/epoch - 11ms/step
Epoch 526/1500
51/51 - 1s - loss: 0.1080 - categorical_accuracy: 0.9589 - val_loss: 1.5456 - val_categorical_accuracy: 0.7908 - 503ms/epoch - 10ms/step
Epoch 527/1500
51/51 - 1s - loss: 0.1082 - categorical_accuracy: 0.9602 - val_loss: 1.6330 - val_categorical_accuracy: 0.8030 - 513ms/epoch - 10ms/step
Epoch 528/1500
51/51 - 0s - loss: 0.1138 - categorical_accuracy: 0.9572 - val_loss: 1.5321 - val_categorical_accuracy: 0.7954 - 494ms/epoch - 10ms/step
Epoch 529/1500
51/51 - 1s - loss: 0.1052 - categorical_accuracy: 0.9607 - val_loss: 1.6025 - val_categorical_accuracy: 0.7860 - 524ms/epoch - 10ms/step
Epoch 530/1500
51/51 - 0s - loss: 0.1096 - categorical_accuracy: 0.9581 - val_loss: 1.5737 - val_categorical_accuracy: 0.7931 - 498ms/epoch - 10ms/step
Epoch 531/1500
51/51 - 1s - loss: 0.1090 - categorical_accuracy: 0.9577 - val_loss: 1.6042 - val_categorical_accuracy: 0.7928 - 536ms/epoch - 11ms/step
Epoch 532/1500
51/51 - 0s - loss: 0.1082 - categorical_accuracy: 0.9595 - val_loss: 1.6533 - val_categorical_accuracy: 0.7841 - 497ms/epoch - 10ms/step
Epoch 533/1500
51/51 - 1s - loss: 0.1113 - categorical_accuracy: 0.9585 - val_loss: 1.6078 - val_categorical_accuracy: 0.7980 - 508ms/epoch - 10ms/step
Epoch 534/1500
51/51 - 0s - loss: 0.1099 - categorical_accuracy: 0.9590 - val_loss: 1.6148 - val_categorical_accuracy: 0.8042 - 491ms/epoch - 10ms/step
Epoch 535/1500
51/51 - 1s - loss: 0.1109 - categorical_accuracy: 0.9575 - val_loss: 1.6080 - val_categorical_accuracy: 0.7986 - 520ms/epoch - 10ms/step
Epoch 536/1500
51/51 - 0s - loss: 0.1131 - categorical_accuracy: 0.9568 - val_loss: 1.6070 - val_categorical_accuracy: 0.7936 - 489ms/epoch - 10ms/step
Epoch 537/1500
51/51 - 1s - loss: 0.1105 - categorical_accuracy: 0.9581 - val_loss: 1.6300 - val_categorical_accuracy: 0.7747 - 506ms/epoch - 10ms/step
Epoch 538/1500
51/51 - 1s - loss: 0.1209 - categorical_accuracy: 0.9555 - val_loss: 3.6195 - val_categorical_accuracy: 0.7687 - 500ms/epoch - 10ms/step
Epoch 539/1500
51/51 - 1s - loss: 0.3985 - categorical_accuracy: 0.8956 - val_loss: 1.3288 - val_categorical_accuracy: 0.7940 - 523ms/epoch - 10ms/step
Epoch 540/1500
51/51 - 0s - loss: 0.1189 - categorical_accuracy: 0.9560 - val_loss: 1.4112 - val_categorical_accuracy: 0.8042 - 489ms/epoch - 10ms/step
Epoch 541/1500
51/51 - 1s - loss: 0.1069 - categorical_accuracy: 0.9602 - val_loss: 1.4879 - val_categorical_accuracy: 0.8012 - 503ms/epoch - 10ms/step
Epoch 542/1500
51/51 - 0s - loss: 0.1264 - categorical_accuracy: 0.9523 - val_loss: 1.5019 - val_categorical_accuracy: 0.8021 - 495ms/epoch - 10ms/step
Epoch 543/1500
51/51 - 1s - loss: 0.1137 - categorical_accuracy: 0.9577 - val_loss: 1.5744 - val_categorical_accuracy: 0.8055 - 507ms/epoch - 10ms/step
Epoch 544/1500
51/51 - 1s - loss: 0.1073 - categorical_accuracy: 0.9600 - val_loss: 1.5407 - val_categorical_accuracy: 0.7990 - 502ms/epoch - 10ms/step
Epoch 545/1500
51/51 - 1s - loss: 0.1077 - categorical_accuracy: 0.9598 - val_loss: 1.5703 - val_categorical_accuracy: 0.8004 - 514ms/epoch - 10ms/step
Epoch 546/1500
51/51 - 0s - loss: 0.1818 - categorical_accuracy: 0.9405 - val_loss: 1.3832 - val_categorical_accuracy: 0.7616 - 470ms/epoch - 9ms/step
Epoch 547/1500
51/51 - 1s - loss: 0.1226 - categorical_accuracy: 0.9534 - val_loss: 1.4933 - val_categorical_accuracy: 0.7989 - 522ms/epoch - 10ms/step
Epoch 548/1500
51/51 - 1s - loss: 0.1011 - categorical_accuracy: 0.9618 - val_loss: 1.5292 - val_categorical_accuracy: 0.7932 - 505ms/epoch - 10ms/step
Epoch 549/1500
51/51 - 1s - loss: 0.1037 - categorical_accuracy: 0.9604 - val_loss: 1.5891 - val_categorical_accuracy: 0.8035 - 502ms/epoch - 10ms/step
Epoch 550/1500
51/51 - 1s - loss: 0.3178 - categorical_accuracy: 0.9138 - val_loss: 1.4077 - val_categorical_accuracy: 0.7988 - 514ms/epoch - 10ms/step
Epoch 551/1500
51/51 - 1s - loss: 0.1100 - categorical_accuracy: 0.9588 - val_loss: 1.4373 - val_categorical_accuracy: 0.7921 - 538ms/epoch - 11ms/step
Epoch 552/1500
51/51 - 0s - loss: 0.1063 - categorical_accuracy: 0.9600 - val_loss: 1.5389 - val_categorical_accuracy: 0.7947 - 492ms/epoch - 10ms/step
Epoch 553/1500
51/51 - 0s - loss: 0.1009 - categorical_accuracy: 0.9624 - val_loss: 1.4914 - val_categorical_accuracy: 0.7995 - 497ms/epoch - 10ms/step
Epoch 554/1500
51/51 - 1s - loss: 0.1018 - categorical_accuracy: 0.9617 - val_loss: 1.5355 - val_categorical_accuracy: 0.7918 - 502ms/epoch - 10ms/step
Epoch 555/1500
51/51 - 1s - loss: 0.0987 - categorical_accuracy: 0.9621 - val_loss: 1.5691 - val_categorical_accuracy: 0.8003 - 504ms/epoch - 10ms/step
Epoch 556/1500
51/51 - 1s - loss: 0.1099 - categorical_accuracy: 0.9589 - val_loss: 1.6195 - val_categorical_accuracy: 0.7846 - 522ms/epoch - 10ms/step
Epoch 557/1500
51/51 - 0s - loss: 0.1177 - categorical_accuracy: 0.9568 - val_loss: 1.5527 - val_categorical_accuracy: 0.7942 - 490ms/epoch - 10ms/step
Epoch 558/1500
51/51 - 0s - loss: 0.1022 - categorical_accuracy: 0.9614 - val_loss: 1.5773 - val_categorical_accuracy: 0.8005 - 492ms/epoch - 10ms/step
Epoch 559/1500
51/51 - 1s - loss: 0.0986 - categorical_accuracy: 0.9631 - val_loss: 1.5829 - val_categorical_accuracy: 0.7972 - 504ms/epoch - 10ms/step
Epoch 560/1500
51/51 - 1s - loss: 0.0987 - categorical_accuracy: 0.9632 - val_loss: 1.6147 - val_categorical_accuracy: 0.7979 - 520ms/epoch - 10ms/step
Epoch 561/1500
51/51 - 1s - loss: 0.1848 - categorical_accuracy: 0.9391 - val_loss: 1.4155 - val_categorical_accuracy: 0.7957 - 525ms/epoch - 10ms/step
Epoch 562/1500
51/51 - 1s - loss: 0.1146 - categorical_accuracy: 0.9567 - val_loss: 1.5218 - val_categorical_accuracy: 0.7855 - 519ms/epoch - 10ms/step
Epoch 563/1500
51/51 - 0s - loss: 0.1015 - categorical_accuracy: 0.9610 - val_loss: 1.5853 - val_categorical_accuracy: 0.8041 - 491ms/epoch - 10ms/step
Epoch 564/1500
51/51 - 0s - loss: 0.0971 - categorical_accuracy: 0.9628 - val_loss: 1.5896 - val_categorical_accuracy: 0.7986 - 493ms/epoch - 10ms/step
Epoch 565/1500
51/51 - 0s - loss: 0.1058 - categorical_accuracy: 0.9598 - val_loss: 1.6233 - val_categorical_accuracy: 0.8006 - 494ms/epoch - 10ms/step
Epoch 566/1500
51/51 - 1s - loss: 0.1068 - categorical_accuracy: 0.9599 - val_loss: 1.5931 - val_categorical_accuracy: 0.8047 - 508ms/epoch - 10ms/step
Epoch 567/1500
51/51 - 0s - loss: 0.1092 - categorical_accuracy: 0.9579 - val_loss: 1.5960 - val_categorical_accuracy: 0.7981 - 494ms/epoch - 10ms/step
Epoch 568/1500
51/51 - 1s - loss: 0.1030 - categorical_accuracy: 0.9609 - val_loss: 1.6406 - val_categorical_accuracy: 0.7980 - 525ms/epoch - 10ms/step
Epoch 569/1500
51/51 - 0s - loss: 0.1015 - categorical_accuracy: 0.9619 - val_loss: 1.6225 - val_categorical_accuracy: 0.7977 - 494ms/epoch - 10ms/step
Epoch 570/1500
51/51 - 1s - loss: 0.1017 - categorical_accuracy: 0.9614 - val_loss: 1.6543 - val_categorical_accuracy: 0.7981 - 521ms/epoch - 10ms/step
Epoch 571/1500
51/51 - 0s - loss: 0.1904 - categorical_accuracy: 0.9408 - val_loss: 1.4680 - val_categorical_accuracy: 0.7221 - 494ms/epoch - 10ms/step
Epoch 572/1500
51/51 - 1s - loss: 0.1465 - categorical_accuracy: 0.9455 - val_loss: 1.5070 - val_categorical_accuracy: 0.7999 - 510ms/epoch - 10ms/step
Epoch 573/1500
51/51 - 0s - loss: 0.1025 - categorical_accuracy: 0.9614 - val_loss: 1.5495 - val_categorical_accuracy: 0.7972 - 489ms/epoch - 10ms/step
Epoch 574/1500
51/51 - 1s - loss: 0.1104 - categorical_accuracy: 0.9583 - val_loss: 1.5725 - val_categorical_accuracy: 0.7968 - 506ms/epoch - 10ms/step
Epoch 575/1500
51/51 - 1s - loss: 0.1042 - categorical_accuracy: 0.9608 - val_loss: 1.6630 - val_categorical_accuracy: 0.7956 - 505ms/epoch - 10ms/step
Epoch 576/1500
51/51 - 1s - loss: 0.0986 - categorical_accuracy: 0.9624 - val_loss: 1.6477 - val_categorical_accuracy: 0.7962 - 524ms/epoch - 10ms/step
Epoch 577/1500
51/51 - 0s - loss: 0.1006 - categorical_accuracy: 0.9610 - val_loss: 1.6476 - val_categorical_accuracy: 0.7965 - 484ms/epoch - 9ms/step
Epoch 578/1500
51/51 - 1s - loss: 0.3202 - categorical_accuracy: 0.9183 - val_loss: 1.1203 - val_categorical_accuracy: 0.7826 - 515ms/epoch - 10ms/step
Epoch 579/1500
51/51 - 0s - loss: 0.1615 - categorical_accuracy: 0.9403 - val_loss: 1.4282 - val_categorical_accuracy: 0.7931 - 494ms/epoch - 10ms/step
Epoch 580/1500
51/51 - 1s - loss: 0.1095 - categorical_accuracy: 0.9583 - val_loss: 1.4572 - val_categorical_accuracy: 0.8006 - 511ms/epoch - 10ms/step
Epoch 581/1500
51/51 - 1s - loss: 0.1000 - categorical_accuracy: 0.9619 - val_loss: 1.5491 - val_categorical_accuracy: 0.7995 - 542ms/epoch - 11ms/step
Epoch 582/1500
51/51 - 1s - loss: 0.0973 - categorical_accuracy: 0.9629 - val_loss: 1.5636 - val_categorical_accuracy: 0.7938 - 523ms/epoch - 10ms/step
Epoch 583/1500
51/51 - 0s - loss: 0.0953 - categorical_accuracy: 0.9634 - val_loss: 1.6265 - val_categorical_accuracy: 0.7984 - 475ms/epoch - 9ms/step
Epoch 584/1500
51/51 - 1s - loss: 0.0999 - categorical_accuracy: 0.9619 - val_loss: 1.6006 - val_categorical_accuracy: 0.7953 - 539ms/epoch - 11ms/step
Epoch 585/1500
51/51 - 0s - loss: 0.1115 - categorical_accuracy: 0.9575 - val_loss: 1.6280 - val_categorical_accuracy: 0.8022 - 493ms/epoch - 10ms/step
Epoch 586/1500
51/51 - 1s - loss: 0.1059 - categorical_accuracy: 0.9599 - val_loss: 1.6732 - val_categorical_accuracy: 0.7989 - 522ms/epoch - 10ms/step
Epoch 587/1500
51/51 - 1s - loss: 0.2470 - categorical_accuracy: 0.9258 - val_loss: 1.4862 - val_categorical_accuracy: 0.8071 - 505ms/epoch - 10ms/step
Epoch 588/1500
51/51 - 1s - loss: 0.0964 - categorical_accuracy: 0.9639 - val_loss: 1.4936 - val_categorical_accuracy: 0.7983 - 541ms/epoch - 11ms/step
Epoch 589/1500
51/51 - 0s - loss: 0.0935 - categorical_accuracy: 0.9637 - val_loss: 1.5798 - val_categorical_accuracy: 0.7966 - 478ms/epoch - 9ms/step
Epoch 590/1500
51/51 - 1s - loss: 0.0935 - categorical_accuracy: 0.9656 - val_loss: 1.6012 - val_categorical_accuracy: 0.8029 - 535ms/epoch - 10ms/step
Epoch 591/1500
51/51 - 0s - loss: 0.0940 - categorical_accuracy: 0.9645 - val_loss: 1.6525 - val_categorical_accuracy: 0.7997 - 476ms/epoch - 9ms/step
Epoch 592/1500
51/51 - 1s - loss: 0.1003 - categorical_accuracy: 0.9620 - val_loss: 1.6560 - val_categorical_accuracy: 0.8037 - 526ms/epoch - 10ms/step
Epoch 593/1500
51/51 - 1s - loss: 0.0926 - categorical_accuracy: 0.9647 - val_loss: 1.6216 - val_categorical_accuracy: 0.7964 - 509ms/epoch - 10ms/step
Epoch 594/1500
51/51 - 1s - loss: 0.1037 - categorical_accuracy: 0.9600 - val_loss: 1.6638 - val_categorical_accuracy: 0.7996 - 571ms/epoch - 11ms/step
Epoch 595/1500
51/51 - 1s - loss: 0.1026 - categorical_accuracy: 0.9612 - val_loss: 1.6383 - val_categorical_accuracy: 0.7945 - 513ms/epoch - 10ms/step
Epoch 596/1500
51/51 - 1s - loss: 0.0962 - categorical_accuracy: 0.9629 - val_loss: 1.6339 - val_categorical_accuracy: 0.7991 - 539ms/epoch - 11ms/step
Epoch 597/1500
51/51 - 1s - loss: 0.0939 - categorical_accuracy: 0.9641 - val_loss: 1.6411 - val_categorical_accuracy: 0.7964 - 552ms/epoch - 11ms/step
Epoch 598/1500
51/51 - 1s - loss: 0.0943 - categorical_accuracy: 0.9646 - val_loss: 1.7187 - val_categorical_accuracy: 0.7998 - 527ms/epoch - 10ms/step
Epoch 599/1500
51/51 - 1s - loss: 0.1065 - categorical_accuracy: 0.9601 - val_loss: 1.6824 - val_categorical_accuracy: 0.7984 - 508ms/epoch - 10ms/step
Epoch 600/1500
51/51 - 1s - loss: 0.1284 - categorical_accuracy: 0.9525 - val_loss: 1.9459 - val_categorical_accuracy: 0.7331 - 514ms/epoch - 10ms/step
Epoch 601/1500
51/51 - 0s - loss: 0.1544 - categorical_accuracy: 0.9448 - val_loss: 1.6054 - val_categorical_accuracy: 0.7879 - 489ms/epoch - 10ms/step
Epoch 602/1500
51/51 - 0s - loss: 0.1065 - categorical_accuracy: 0.9592 - val_loss: 1.6194 - val_categorical_accuracy: 0.7904 - 489ms/epoch - 10ms/step
Epoch 603/1500
51/51 - 1s - loss: 0.1046 - categorical_accuracy: 0.9613 - val_loss: 1.6400 - val_categorical_accuracy: 0.7952 - 505ms/epoch - 10ms/step
Epoch 604/1500
51/51 - 1s - loss: 0.1032 - categorical_accuracy: 0.9600 - val_loss: 1.6362 - val_categorical_accuracy: 0.7894 - 501ms/epoch - 10ms/step
Epoch 605/1500
51/51 - 1s - loss: 0.1016 - categorical_accuracy: 0.9620 - val_loss: 1.6974 - val_categorical_accuracy: 0.7998 - 520ms/epoch - 10ms/step
Epoch 606/1500
51/51 - 0s - loss: 0.0902 - categorical_accuracy: 0.9651 - val_loss: 1.6897 - val_categorical_accuracy: 0.7993 - 489ms/epoch - 10ms/step
Epoch 607/1500
51/51 - 0s - loss: 0.1049 - categorical_accuracy: 0.9606 - val_loss: 1.6870 - val_categorical_accuracy: 0.7937 - 493ms/epoch - 10ms/step
Epoch 608/1500
51/51 - 0s - loss: 0.0935 - categorical_accuracy: 0.9650 - val_loss: 1.7433 - val_categorical_accuracy: 0.7997 - 494ms/epoch - 10ms/step
Epoch 609/1500
51/51 - 1s - loss: 0.1004 - categorical_accuracy: 0.9616 - val_loss: 1.8157 - val_categorical_accuracy: 0.7809 - 516ms/epoch - 10ms/step
Epoch 610/1500
51/51 - 1s - loss: 0.1509 - categorical_accuracy: 0.9489 - val_loss: 1.6432 - val_categorical_accuracy: 0.7964 - 505ms/epoch - 10ms/step
Epoch 611/1500
51/51 - 1s - loss: 0.0943 - categorical_accuracy: 0.9641 - val_loss: 1.6963 - val_categorical_accuracy: 0.7970 - 522ms/epoch - 10ms/step
Epoch 612/1500
51/51 - 0s - loss: 0.1010 - categorical_accuracy: 0.9607 - val_loss: 1.6727 - val_categorical_accuracy: 0.7765 - 493ms/epoch - 10ms/step
Epoch 613/1500
51/51 - 1s - loss: 0.1171 - categorical_accuracy: 0.9557 - val_loss: 1.7424 - val_categorical_accuracy: 0.8005 - 502ms/epoch - 10ms/step
Epoch 614/1500
51/51 - 0s - loss: 0.0979 - categorical_accuracy: 0.9637 - val_loss: 1.6737 - val_categorical_accuracy: 0.7892 - 486ms/epoch - 10ms/step
Epoch 615/1500
51/51 - 1s - loss: 0.0919 - categorical_accuracy: 0.9650 - val_loss: 1.7240 - val_categorical_accuracy: 0.7979 - 527ms/epoch - 10ms/step
Epoch 616/1500
51/51 - 0s - loss: 0.1050 - categorical_accuracy: 0.9596 - val_loss: 2.2332 - val_categorical_accuracy: 0.6937 - 490ms/epoch - 10ms/step
Epoch 617/1500
51/51 - 1s - loss: 0.3820 - categorical_accuracy: 0.9009 - val_loss: 1.4163 - val_categorical_accuracy: 0.7953 - 508ms/epoch - 10ms/step
Epoch 618/1500
51/51 - 0s - loss: 0.1069 - categorical_accuracy: 0.9591 - val_loss: 1.5046 - val_categorical_accuracy: 0.8015 - 492ms/epoch - 10ms/step
Epoch 619/1500
51/51 - 1s - loss: 0.0942 - categorical_accuracy: 0.9649 - val_loss: 1.5713 - val_categorical_accuracy: 0.7918 - 509ms/epoch - 10ms/step
Epoch 620/1500
51/51 - 1s - loss: 0.0929 - categorical_accuracy: 0.9653 - val_loss: 1.6458 - val_categorical_accuracy: 0.7950 - 511ms/epoch - 10ms/step
Epoch 621/1500
51/51 - 1s - loss: 0.0911 - categorical_accuracy: 0.9666 - val_loss: 1.6484 - val_categorical_accuracy: 0.7944 - 518ms/epoch - 10ms/step
Epoch 622/1500
51/51 - 0s - loss: 0.0946 - categorical_accuracy: 0.9653 - val_loss: 1.6906 - val_categorical_accuracy: 0.7980 - 496ms/epoch - 10ms/step
Epoch 623/1500
51/51 - 1s - loss: 0.0910 - categorical_accuracy: 0.9642 - val_loss: 1.6938 - val_categorical_accuracy: 0.7944 - 520ms/epoch - 10ms/step
Epoch 624/1500
51/51 - 0s - loss: 0.1003 - categorical_accuracy: 0.9627 - val_loss: 1.6818 - val_categorical_accuracy: 0.7908 - 491ms/epoch - 10ms/step
Epoch 625/1500
51/51 - 1s - loss: 0.0970 - categorical_accuracy: 0.9632 - val_loss: 1.7534 - val_categorical_accuracy: 0.7916 - 515ms/epoch - 10ms/step
Epoch 626/1500
51/51 - 0s - loss: 0.0933 - categorical_accuracy: 0.9647 - val_loss: 1.7234 - val_categorical_accuracy: 0.7981 - 470ms/epoch - 9ms/step
Epoch 627/1500
51/51 - 1s - loss: 0.0918 - categorical_accuracy: 0.9643 - val_loss: 1.7181 - val_categorical_accuracy: 0.8003 - 522ms/epoch - 10ms/step
Epoch 628/1500
51/51 - 0s - loss: 0.0928 - categorical_accuracy: 0.9650 - val_loss: 1.7379 - val_categorical_accuracy: 0.7887 - 482ms/epoch - 9ms/step
Epoch 629/1500
51/51 - 1s - loss: 0.1068 - categorical_accuracy: 0.9595 - val_loss: 1.6927 - val_categorical_accuracy: 0.7868 - 515ms/epoch - 10ms/step
Epoch 630/1500
51/51 - 0s - loss: 0.0988 - categorical_accuracy: 0.9625 - val_loss: 1.7588 - val_categorical_accuracy: 0.7897 - 486ms/epoch - 10ms/step
Epoch 631/1500
51/51 - 1s - loss: 0.0941 - categorical_accuracy: 0.9634 - val_loss: 1.7624 - val_categorical_accuracy: 0.7930 - 520ms/epoch - 10ms/step
Epoch 632/1500
51/51 - 0s - loss: 0.0931 - categorical_accuracy: 0.9641 - val_loss: 1.7412 - val_categorical_accuracy: 0.7821 - 458ms/epoch - 9ms/step
Epoch 633/1500
51/51 - 1s - loss: 0.0922 - categorical_accuracy: 0.9654 - val_loss: 1.7240 - val_categorical_accuracy: 0.7969 - 553ms/epoch - 11ms/step
Epoch 634/1500
51/51 - 0s - loss: 0.0970 - categorical_accuracy: 0.9632 - val_loss: 1.7683 - val_categorical_accuracy: 0.7928 - 492ms/epoch - 10ms/step
Epoch 635/1500
51/51 - 1s - loss: 0.0976 - categorical_accuracy: 0.9641 - val_loss: 1.8482 - val_categorical_accuracy: 0.7736 - 517ms/epoch - 10ms/step
Epoch 636/1500
51/51 - 0s - loss: 0.1509 - categorical_accuracy: 0.9451 - val_loss: 1.6742 - val_categorical_accuracy: 0.7928 - 479ms/epoch - 9ms/step
Epoch 637/1500
51/51 - 1s - loss: 0.0999 - categorical_accuracy: 0.9618 - val_loss: 1.7026 - val_categorical_accuracy: 0.7848 - 516ms/epoch - 10ms/step
Epoch 638/1500
51/51 - 0s - loss: 0.0935 - categorical_accuracy: 0.9642 - val_loss: 1.7556 - val_categorical_accuracy: 0.7992 - 466ms/epoch - 9ms/step
Epoch 639/1500
51/51 - 1s - loss: 0.0941 - categorical_accuracy: 0.9642 - val_loss: 1.7478 - val_categorical_accuracy: 0.7914 - 506ms/epoch - 10ms/step
Epoch 640/1500
51/51 - 1s - loss: 0.0903 - categorical_accuracy: 0.9655 - val_loss: 1.7015 - val_categorical_accuracy: 0.7950 - 521ms/epoch - 10ms/step
Epoch 641/1500
51/51 - 1s - loss: 0.0952 - categorical_accuracy: 0.9632 - val_loss: 1.7960 - val_categorical_accuracy: 0.7957 - 519ms/epoch - 10ms/step
Epoch 642/1500
51/51 - 0s - loss: 0.0962 - categorical_accuracy: 0.9641 - val_loss: 1.7735 - val_categorical_accuracy: 0.7928 - 476ms/epoch - 9ms/step
Epoch 643/1500
51/51 - 1s - loss: 0.0977 - categorical_accuracy: 0.9632 - val_loss: 1.8195 - val_categorical_accuracy: 0.8013 - 518ms/epoch - 10ms/step
Epoch 644/1500
51/51 - 0s - loss: 0.0940 - categorical_accuracy: 0.9645 - val_loss: 1.8182 - val_categorical_accuracy: 0.7991 - 470ms/epoch - 9ms/step
Epoch 645/1500
51/51 - 1s - loss: 0.2158 - categorical_accuracy: 0.9374 - val_loss: 1.5766 - val_categorical_accuracy: 0.7990 - 523ms/epoch - 10ms/step
Epoch 646/1500
51/51 - 0s - loss: 0.1036 - categorical_accuracy: 0.9613 - val_loss: 1.6982 - val_categorical_accuracy: 0.7966 - 499ms/epoch - 10ms/step
Epoch 647/1500
51/51 - 1s - loss: 0.0991 - categorical_accuracy: 0.9624 - val_loss: 1.7126 - val_categorical_accuracy: 0.7803 - 523ms/epoch - 10ms/step
Epoch 648/1500
51/51 - 0s - loss: 0.1299 - categorical_accuracy: 0.9525 - val_loss: 1.6707 - val_categorical_accuracy: 0.7923 - 493ms/epoch - 10ms/step
Epoch 649/1500
51/51 - 1s - loss: 0.0896 - categorical_accuracy: 0.9653 - val_loss: 1.7798 - val_categorical_accuracy: 0.7859 - 525ms/epoch - 10ms/step
Epoch 650/1500
51/51 - 0s - loss: 0.1009 - categorical_accuracy: 0.9623 - val_loss: 1.7165 - val_categorical_accuracy: 0.7947 - 475ms/epoch - 9ms/step
Epoch 651/1500
51/51 - 1s - loss: 0.0936 - categorical_accuracy: 0.9639 - val_loss: 1.7539 - val_categorical_accuracy: 0.7980 - 517ms/epoch - 10ms/step
Epoch 652/1500
51/51 - 0s - loss: 0.0904 - categorical_accuracy: 0.9651 - val_loss: 1.7514 - val_categorical_accuracy: 0.7918 - 473ms/epoch - 9ms/step
Epoch 653/1500
51/51 - 1s - loss: 0.0934 - categorical_accuracy: 0.9647 - val_loss: 1.7348 - val_categorical_accuracy: 0.7909 - 505ms/epoch - 10ms/step
Epoch 654/1500
51/51 - 0s - loss: 0.0920 - categorical_accuracy: 0.9647 - val_loss: 1.8828 - val_categorical_accuracy: 0.7836 - 488ms/epoch - 10ms/step
Epoch 655/1500
51/51 - 1s - loss: 0.1123 - categorical_accuracy: 0.9583 - val_loss: 3.0208 - val_categorical_accuracy: 0.7395 - 820ms/epoch - 16ms/step
Epoch 656/1500
51/51 - 1s - loss: 0.2237 - categorical_accuracy: 0.9318 - val_loss: 1.6345 - val_categorical_accuracy: 0.7929 - 537ms/epoch - 11ms/step
Epoch 657/1500
51/51 - 1s - loss: 0.0941 - categorical_accuracy: 0.9636 - val_loss: 1.6289 - val_categorical_accuracy: 0.7958 - 510ms/epoch - 10ms/step
Epoch 658/1500
51/51 - 1s - loss: 0.0869 - categorical_accuracy: 0.9675 - val_loss: 1.7212 - val_categorical_accuracy: 0.7995 - 537ms/epoch - 11ms/step
Epoch 659/1500
51/51 - 1s - loss: 0.0852 - categorical_accuracy: 0.9681 - val_loss: 1.7573 - val_categorical_accuracy: 0.7938 - 509ms/epoch - 10ms/step
Epoch 660/1500
51/51 - 1s - loss: 0.0893 - categorical_accuracy: 0.9654 - val_loss: 1.7525 - val_categorical_accuracy: 0.7992 - 539ms/epoch - 11ms/step
Epoch 661/1500
51/51 - 1s - loss: 0.0940 - categorical_accuracy: 0.9636 - val_loss: 1.7487 - val_categorical_accuracy: 0.7961 - 507ms/epoch - 10ms/step
Epoch 662/1500
51/51 - 1s - loss: 0.0915 - categorical_accuracy: 0.9646 - val_loss: 1.8250 - val_categorical_accuracy: 0.8001 - 522ms/epoch - 10ms/step
Epoch 663/1500
51/51 - 0s - loss: 0.0889 - categorical_accuracy: 0.9662 - val_loss: 1.7571 - val_categorical_accuracy: 0.7983 - 495ms/epoch - 10ms/step
Epoch 664/1500
51/51 - 1s - loss: 0.0871 - categorical_accuracy: 0.9662 - val_loss: 1.8473 - val_categorical_accuracy: 0.7998 - 520ms/epoch - 10ms/step
Epoch 665/1500
51/51 - 0s - loss: 0.2173 - categorical_accuracy: 0.9401 - val_loss: 1.5856 - val_categorical_accuracy: 0.7051 - 498ms/epoch - 10ms/step
Epoch 666/1500
51/51 - 1s - loss: 0.1701 - categorical_accuracy: 0.9390 - val_loss: 1.5391 - val_categorical_accuracy: 0.8014 - 549ms/epoch - 11ms/step
Epoch 667/1500
51/51 - 1s - loss: 0.0923 - categorical_accuracy: 0.9639 - val_loss: 1.6715 - val_categorical_accuracy: 0.7946 - 503ms/epoch - 10ms/step
Epoch 668/1500
51/51 - 1s - loss: 0.0892 - categorical_accuracy: 0.9660 - val_loss: 1.7120 - val_categorical_accuracy: 0.7942 - 526ms/epoch - 10ms/step
Epoch 669/1500
51/51 - 1s - loss: 0.0891 - categorical_accuracy: 0.9660 - val_loss: 1.7221 - val_categorical_accuracy: 0.7961 - 504ms/epoch - 10ms/step
Epoch 670/1500
51/51 - 1s - loss: 0.0848 - categorical_accuracy: 0.9670 - val_loss: 1.7606 - val_categorical_accuracy: 0.7949 - 536ms/epoch - 11ms/step
Epoch 671/1500
51/51 - 1s - loss: 0.0833 - categorical_accuracy: 0.9682 - val_loss: 1.7654 - val_categorical_accuracy: 0.7953 - 523ms/epoch - 10ms/step
Epoch 672/1500
51/51 - 1s - loss: 0.0897 - categorical_accuracy: 0.9649 - val_loss: 1.7751 - val_categorical_accuracy: 0.7931 - 519ms/epoch - 10ms/step
Epoch 673/1500
51/51 - 1s - loss: 0.3311 - categorical_accuracy: 0.9120 - val_loss: 1.4833 - val_categorical_accuracy: 0.7967 - 536ms/epoch - 11ms/step
Epoch 674/1500
51/51 - 1s - loss: 0.1015 - categorical_accuracy: 0.9625 - val_loss: 1.6023 - val_categorical_accuracy: 0.7998 - 504ms/epoch - 10ms/step
Epoch 675/1500
51/51 - 1s - loss: 0.0865 - categorical_accuracy: 0.9685 - val_loss: 1.6662 - val_categorical_accuracy: 0.7932 - 535ms/epoch - 10ms/step
Epoch 676/1500
51/51 - 1s - loss: 0.0887 - categorical_accuracy: 0.9651 - val_loss: 1.8555 - val_categorical_accuracy: 0.7662 - 510ms/epoch - 10ms/step
Epoch 677/1500
51/51 - 1s - loss: 0.0897 - categorical_accuracy: 0.9658 - val_loss: 1.7602 - val_categorical_accuracy: 0.8024 - 527ms/epoch - 10ms/step
Epoch 678/1500
51/51 - 1s - loss: 0.0827 - categorical_accuracy: 0.9680 - val_loss: 1.7087 - val_categorical_accuracy: 0.7904 - 546ms/epoch - 11ms/step
Epoch 679/1500
51/51 - 1s - loss: 0.0879 - categorical_accuracy: 0.9666 - val_loss: 1.7799 - val_categorical_accuracy: 0.8012 - 534ms/epoch - 10ms/step
Epoch 680/1500
51/51 - 1s - loss: 0.0874 - categorical_accuracy: 0.9672 - val_loss: 1.7712 - val_categorical_accuracy: 0.7961 - 501ms/epoch - 10ms/step
Epoch 681/1500
51/51 - 1s - loss: 0.0829 - categorical_accuracy: 0.9681 - val_loss: 1.7900 - val_categorical_accuracy: 0.7953 - 531ms/epoch - 10ms/step
Epoch 682/1500
51/51 - 0s - loss: 0.0885 - categorical_accuracy: 0.9662 - val_loss: 1.7958 - val_categorical_accuracy: 0.7930 - 493ms/epoch - 10ms/step
Epoch 683/1500
51/51 - 1s - loss: 0.0847 - categorical_accuracy: 0.9679 - val_loss: 1.8404 - val_categorical_accuracy: 0.7937 - 525ms/epoch - 10ms/step
Epoch 684/1500
51/51 - 1s - loss: 0.1029 - categorical_accuracy: 0.9616 - val_loss: 1.6922 - val_categorical_accuracy: 0.7858 - 507ms/epoch - 10ms/step
Epoch 685/1500
51/51 - 1s - loss: 0.0999 - categorical_accuracy: 0.9614 - val_loss: 1.7751 - val_categorical_accuracy: 0.7919 - 532ms/epoch - 10ms/step
Epoch 686/1500
51/51 - 0s - loss: 0.0969 - categorical_accuracy: 0.9619 - val_loss: 1.7944 - val_categorical_accuracy: 0.7809 - 490ms/epoch - 10ms/step
Epoch 687/1500
51/51 - 1s - loss: 0.0901 - categorical_accuracy: 0.9651 - val_loss: 1.7894 - val_categorical_accuracy: 0.7983 - 535ms/epoch - 10ms/step
Epoch 688/1500
51/51 - 1s - loss: 0.0989 - categorical_accuracy: 0.9624 - val_loss: 1.7868 - val_categorical_accuracy: 0.7967 - 505ms/epoch - 10ms/step
Epoch 689/1500
51/51 - 1s - loss: 0.0861 - categorical_accuracy: 0.9661 - val_loss: 1.8617 - val_categorical_accuracy: 0.7999 - 522ms/epoch - 10ms/step
Epoch 690/1500
51/51 - 1s - loss: 0.0827 - categorical_accuracy: 0.9673 - val_loss: 1.8378 - val_categorical_accuracy: 0.7978 - 549ms/epoch - 11ms/step
Epoch 691/1500
51/51 - 1s - loss: 0.0921 - categorical_accuracy: 0.9655 - val_loss: 1.8570 - val_categorical_accuracy: 0.7887 - 564ms/epoch - 11ms/step
Epoch 692/1500
51/51 - 1s - loss: 0.2007 - categorical_accuracy: 0.9384 - val_loss: 1.5918 - val_categorical_accuracy: 0.7970 - 525ms/epoch - 10ms/step
Epoch 693/1500
51/51 - 1s - loss: 0.1085 - categorical_accuracy: 0.9593 - val_loss: 1.7089 - val_categorical_accuracy: 0.7890 - 555ms/epoch - 11ms/step
Epoch 694/1500
51/51 - 1s - loss: 0.0890 - categorical_accuracy: 0.9655 - val_loss: 1.7499 - val_categorical_accuracy: 0.7932 - 554ms/epoch - 11ms/step
Epoch 695/1500
51/51 - 1s - loss: 0.0882 - categorical_accuracy: 0.9659 - val_loss: 1.8180 - val_categorical_accuracy: 0.8000 - 541ms/epoch - 11ms/step
Epoch 696/1500
51/51 - 1s - loss: 0.0826 - categorical_accuracy: 0.9685 - val_loss: 1.8096 - val_categorical_accuracy: 0.7947 - 575ms/epoch - 11ms/step
Epoch 697/1500
51/51 - 1s - loss: 0.0884 - categorical_accuracy: 0.9660 - val_loss: 1.8349 - val_categorical_accuracy: 0.8006 - 580ms/epoch - 11ms/step
Epoch 698/1500
51/51 - 1s - loss: 0.0857 - categorical_accuracy: 0.9668 - val_loss: 1.8041 - val_categorical_accuracy: 0.7966 - 569ms/epoch - 11ms/step
Epoch 699/1500
51/51 - 1s - loss: 0.0894 - categorical_accuracy: 0.9662 - val_loss: 1.8534 - val_categorical_accuracy: 0.8018 - 553ms/epoch - 11ms/step
Epoch 700/1500
51/51 - 1s - loss: 0.0887 - categorical_accuracy: 0.9663 - val_loss: 1.9109 - val_categorical_accuracy: 0.8025 - 556ms/epoch - 11ms/step
Epoch 701/1500
51/51 - 1s - loss: 0.1989 - categorical_accuracy: 0.9352 - val_loss: 1.6283 - val_categorical_accuracy: 0.7857 - 567ms/epoch - 11ms/step
Epoch 702/1500
51/51 - 1s - loss: 0.1029 - categorical_accuracy: 0.9617 - val_loss: 1.7062 - val_categorical_accuracy: 0.7891 - 573ms/epoch - 11ms/step
Epoch 703/1500
51/51 - 1s - loss: 0.0853 - categorical_accuracy: 0.9680 - val_loss: 1.7563 - val_categorical_accuracy: 0.7915 - 566ms/epoch - 11ms/step
Epoch 704/1500
51/51 - 1s - loss: 0.0848 - categorical_accuracy: 0.9675 - val_loss: 1.8489 - val_categorical_accuracy: 0.7989 - 575ms/epoch - 11ms/step
Epoch 705/1500
51/51 - 1s - loss: 0.0885 - categorical_accuracy: 0.9661 - val_loss: 1.8443 - val_categorical_accuracy: 0.7822 - 572ms/epoch - 11ms/step
Epoch 706/1500
51/51 - 1s - loss: 0.1866 - categorical_accuracy: 0.9370 - val_loss: 1.6936 - val_categorical_accuracy: 0.7914 - 553ms/epoch - 11ms/step
Epoch 707/1500
51/51 - 1s - loss: 0.0897 - categorical_accuracy: 0.9661 - val_loss: 1.7714 - val_categorical_accuracy: 0.7995 - 569ms/epoch - 11ms/step
Epoch 708/1500
51/51 - 1s - loss: 0.0839 - categorical_accuracy: 0.9679 - val_loss: 1.7791 - val_categorical_accuracy: 0.7944 - 557ms/epoch - 11ms/step
Epoch 709/1500
51/51 - 1s - loss: 0.0810 - categorical_accuracy: 0.9693 - val_loss: 1.7663 - val_categorical_accuracy: 0.7932 - 540ms/epoch - 11ms/step
Epoch 710/1500
51/51 - 1s - loss: 0.0849 - categorical_accuracy: 0.9669 - val_loss: 1.8108 - val_categorical_accuracy: 0.7950 - 571ms/epoch - 11ms/step
Epoch 711/1500
51/51 - 1s - loss: 0.0795 - categorical_accuracy: 0.9699 - val_loss: 1.8600 - val_categorical_accuracy: 0.7798 - 526ms/epoch - 10ms/step
Epoch 712/1500
51/51 - 1s - loss: 0.0832 - categorical_accuracy: 0.9690 - val_loss: 1.8241 - val_categorical_accuracy: 0.7983 - 571ms/epoch - 11ms/step
Epoch 713/1500
51/51 - 1s - loss: 0.0770 - categorical_accuracy: 0.9706 - val_loss: 1.8919 - val_categorical_accuracy: 0.7972 - 542ms/epoch - 11ms/step
Epoch 714/1500
51/51 - 1s - loss: 0.0815 - categorical_accuracy: 0.9685 - val_loss: 1.8157 - val_categorical_accuracy: 0.7940 - 545ms/epoch - 11ms/step
Epoch 715/1500
51/51 - 1s - loss: 0.0888 - categorical_accuracy: 0.9666 - val_loss: 1.8614 - val_categorical_accuracy: 0.7928 - 564ms/epoch - 11ms/step
Epoch 716/1500
51/51 - 1s - loss: 0.0877 - categorical_accuracy: 0.9658 - val_loss: 1.9098 - val_categorical_accuracy: 0.7807 - 559ms/epoch - 11ms/step
Epoch 717/1500
51/51 - 1s - loss: 0.2682 - categorical_accuracy: 0.9195 - val_loss: 1.6222 - val_categorical_accuracy: 0.7934 - 542ms/epoch - 11ms/step
Epoch 718/1500
51/51 - 1s - loss: 0.0944 - categorical_accuracy: 0.9638 - val_loss: 1.7206 - val_categorical_accuracy: 0.7835 - 551ms/epoch - 11ms/step
Epoch 719/1500
51/51 - 1s - loss: 0.0839 - categorical_accuracy: 0.9683 - val_loss: 1.7471 - val_categorical_accuracy: 0.7864 - 524ms/epoch - 10ms/step
Epoch 720/1500
51/51 - 1s - loss: 0.0825 - categorical_accuracy: 0.9687 - val_loss: 1.7416 - val_categorical_accuracy: 0.7858 - 504ms/epoch - 10ms/step
Epoch 721/1500
51/51 - 1s - loss: 0.0819 - categorical_accuracy: 0.9689 - val_loss: 1.8269 - val_categorical_accuracy: 0.7946 - 540ms/epoch - 11ms/step
Epoch 722/1500
51/51 - 0s - loss: 0.0822 - categorical_accuracy: 0.9685 - val_loss: 1.8579 - val_categorical_accuracy: 0.7927 - 499ms/epoch - 10ms/step
Epoch 723/1500
51/51 - 1s - loss: 0.0859 - categorical_accuracy: 0.9661 - val_loss: 1.8832 - val_categorical_accuracy: 0.8015 - 541ms/epoch - 11ms/step
Epoch 724/1500
51/51 - 1s - loss: 0.0847 - categorical_accuracy: 0.9673 - val_loss: 1.8507 - val_categorical_accuracy: 0.7936 - 509ms/epoch - 10ms/step
Epoch 725/1500
51/51 - 1s - loss: 0.0933 - categorical_accuracy: 0.9636 - val_loss: 1.8385 - val_categorical_accuracy: 0.7848 - 537ms/epoch - 11ms/step
Epoch 726/1500
51/51 - 0s - loss: 0.0963 - categorical_accuracy: 0.9624 - val_loss: 1.8060 - val_categorical_accuracy: 0.7912 - 477ms/epoch - 9ms/step
Epoch 727/1500
51/51 - 1s - loss: 0.0845 - categorical_accuracy: 0.9671 - val_loss: 1.8586 - val_categorical_accuracy: 0.7948 - 522ms/epoch - 10ms/step
Epoch 728/1500
51/51 - 1s - loss: 0.0795 - categorical_accuracy: 0.9691 - val_loss: 1.8365 - val_categorical_accuracy: 0.7940 - 507ms/epoch - 10ms/step
Epoch 729/1500
51/51 - 1s - loss: 0.0928 - categorical_accuracy: 0.9646 - val_loss: 1.8734 - val_categorical_accuracy: 0.7868 - 532ms/epoch - 10ms/step
Epoch 730/1500
51/51 - 0s - loss: 0.0833 - categorical_accuracy: 0.9678 - val_loss: 1.8715 - val_categorical_accuracy: 0.7879 - 495ms/epoch - 10ms/step
Epoch 731/1500
51/51 - 1s - loss: 0.0809 - categorical_accuracy: 0.9689 - val_loss: 1.9213 - val_categorical_accuracy: 0.7926 - 519ms/epoch - 10ms/step
Epoch 732/1500
51/51 - 0s - loss: 0.0937 - categorical_accuracy: 0.9642 - val_loss: 1.8482 - val_categorical_accuracy: 0.7849 - 476ms/epoch - 9ms/step
Epoch 733/1500
51/51 - 1s - loss: 0.1043 - categorical_accuracy: 0.9620 - val_loss: 1.8930 - val_categorical_accuracy: 0.7971 - 553ms/epoch - 11ms/step
Epoch 734/1500
51/51 - 1s - loss: 0.0820 - categorical_accuracy: 0.9683 - val_loss: 1.9134 - val_categorical_accuracy: 0.7961 - 506ms/epoch - 10ms/step
Epoch 735/1500
51/51 - 1s - loss: 0.0837 - categorical_accuracy: 0.9681 - val_loss: 1.9165 - val_categorical_accuracy: 0.7930 - 524ms/epoch - 10ms/step
Epoch 736/1500
51/51 - 1s - loss: 0.3035 - categorical_accuracy: 0.9208 - val_loss: 1.4796 - val_categorical_accuracy: 0.7902 - 502ms/epoch - 10ms/step
Epoch 737/1500
51/51 - 1s - loss: 0.1040 - categorical_accuracy: 0.9608 - val_loss: 1.6871 - val_categorical_accuracy: 0.7962 - 522ms/epoch - 10ms/step
Epoch 738/1500
51/51 - 0s - loss: 0.0868 - categorical_accuracy: 0.9666 - val_loss: 1.7765 - val_categorical_accuracy: 0.7910 - 475ms/epoch - 9ms/step
Epoch 739/1500
51/51 - 1s - loss: 0.0799 - categorical_accuracy: 0.9694 - val_loss: 1.7994 - val_categorical_accuracy: 0.8008 - 526ms/epoch - 10ms/step
Epoch 740/1500
51/51 - 0s - loss: 0.0842 - categorical_accuracy: 0.9678 - val_loss: 1.8054 - val_categorical_accuracy: 0.7915 - 494ms/epoch - 10ms/step
Epoch 741/1500
51/51 - 1s - loss: 0.0793 - categorical_accuracy: 0.9692 - val_loss: 1.8906 - val_categorical_accuracy: 0.8005 - 539ms/epoch - 11ms/step
Epoch 742/1500
51/51 - 1s - loss: 0.0819 - categorical_accuracy: 0.9678 - val_loss: 1.8707 - val_categorical_accuracy: 0.7963 - 524ms/epoch - 10ms/step
Epoch 743/1500
51/51 - 1s - loss: 0.0867 - categorical_accuracy: 0.9678 - val_loss: 1.8923 - val_categorical_accuracy: 0.7950 - 524ms/epoch - 10ms/step
Epoch 744/1500
51/51 - 1s - loss: 0.0799 - categorical_accuracy: 0.9705 - val_loss: 1.9049 - val_categorical_accuracy: 0.7823 - 508ms/epoch - 10ms/step
Epoch 745/1500
51/51 - 1s - loss: 0.0832 - categorical_accuracy: 0.9678 - val_loss: 1.8902 - val_categorical_accuracy: 0.7908 - 524ms/epoch - 10ms/step
Epoch 746/1500
51/51 - 1s - loss: 0.0813 - categorical_accuracy: 0.9693 - val_loss: 1.9097 - val_categorical_accuracy: 0.7879 - 526ms/epoch - 10ms/step
Epoch 747/1500
51/51 - 1s - loss: 0.0858 - categorical_accuracy: 0.9670 - val_loss: 1.8954 - val_categorical_accuracy: 0.7910 - 524ms/epoch - 10ms/step
Epoch 748/1500
51/51 - 1s - loss: 0.0893 - categorical_accuracy: 0.9661 - val_loss: 1.9190 - val_categorical_accuracy: 0.7891 - 538ms/epoch - 11ms/step
Epoch 749/1500
51/51 - 1s - loss: 0.0859 - categorical_accuracy: 0.9673 - val_loss: 1.8873 - val_categorical_accuracy: 0.7941 - 507ms/epoch - 10ms/step
Epoch 750/1500
51/51 - 1s - loss: 0.0893 - categorical_accuracy: 0.9654 - val_loss: 1.9053 - val_categorical_accuracy: 0.7970 - 531ms/epoch - 10ms/step
Epoch 751/1500
51/51 - 1s - loss: 0.0823 - categorical_accuracy: 0.9678 - val_loss: 1.9134 - val_categorical_accuracy: 0.7967 - 512ms/epoch - 10ms/step
Epoch 752/1500
51/51 - 1s - loss: 0.0787 - categorical_accuracy: 0.9697 - val_loss: 1.9683 - val_categorical_accuracy: 0.7935 - 550ms/epoch - 11ms/step
Epoch 753/1500
51/51 - 1s - loss: 0.0857 - categorical_accuracy: 0.9675 - val_loss: 1.9408 - val_categorical_accuracy: 0.7972 - 524ms/epoch - 10ms/step
Epoch 754/1500
51/51 - 1s - loss: 0.0834 - categorical_accuracy: 0.9671 - val_loss: 1.9580 - val_categorical_accuracy: 0.7932 - 539ms/epoch - 11ms/step
Epoch 755/1500
51/51 - 1s - loss: 0.0877 - categorical_accuracy: 0.9671 - val_loss: 1.9261 - val_categorical_accuracy: 0.7957 - 520ms/epoch - 10ms/step
Epoch 756/1500
51/51 - 1s - loss: 0.0856 - categorical_accuracy: 0.9670 - val_loss: 1.8795 - val_categorical_accuracy: 0.7905 - 534ms/epoch - 10ms/step
Epoch 757/1500
51/51 - 1s - loss: 0.0846 - categorical_accuracy: 0.9675 - val_loss: 1.9618 - val_categorical_accuracy: 0.7872 - 522ms/epoch - 10ms/step
Epoch 758/1500
51/51 - 1s - loss: 0.3050 - categorical_accuracy: 0.9176 - val_loss: 1.6973 - val_categorical_accuracy: 0.8015 - 520ms/epoch - 10ms/step
Epoch 759/1500
51/51 - 1s - loss: 0.0927 - categorical_accuracy: 0.9641 - val_loss: 1.7599 - val_categorical_accuracy: 0.7941 - 505ms/epoch - 10ms/step
Epoch 760/1500
51/51 - 1s - loss: 0.0839 - categorical_accuracy: 0.9679 - val_loss: 1.7861 - val_categorical_accuracy: 0.7962 - 522ms/epoch - 10ms/step
Epoch 761/1500
51/51 - 1s - loss: 0.0748 - categorical_accuracy: 0.9715 - val_loss: 1.8609 - val_categorical_accuracy: 0.7895 - 523ms/epoch - 10ms/step
Epoch 762/1500
51/51 - 0s - loss: 0.0773 - categorical_accuracy: 0.9703 - val_loss: 1.9301 - val_categorical_accuracy: 0.7912 - 492ms/epoch - 10ms/step
Epoch 763/1500
51/51 - 1s - loss: 0.0818 - categorical_accuracy: 0.9681 - val_loss: 1.9003 - val_categorical_accuracy: 0.7892 - 509ms/epoch - 10ms/step
Epoch 764/1500
51/51 - 1s - loss: 0.0788 - categorical_accuracy: 0.9700 - val_loss: 1.9147 - val_categorical_accuracy: 0.7988 - 518ms/epoch - 10ms/step
Epoch 765/1500
51/51 - 1s - loss: 0.0769 - categorical_accuracy: 0.9715 - val_loss: 1.9267 - val_categorical_accuracy: 0.7898 - 522ms/epoch - 10ms/step
Epoch 766/1500
51/51 - 1s - loss: 0.0897 - categorical_accuracy: 0.9665 - val_loss: 1.9620 - val_categorical_accuracy: 0.7720 - 510ms/epoch - 10ms/step
Epoch 767/1500
51/51 - 1s - loss: 0.0876 - categorical_accuracy: 0.9674 - val_loss: 1.9183 - val_categorical_accuracy: 0.7955 - 512ms/epoch - 10ms/step
Epoch 768/1500
51/51 - 0s - loss: 0.0819 - categorical_accuracy: 0.9681 - val_loss: 2.0056 - val_categorical_accuracy: 0.7971 - 491ms/epoch - 10ms/step
Epoch 769/1500
51/51 - 1s - loss: 0.0863 - categorical_accuracy: 0.9668 - val_loss: 1.9745 - val_categorical_accuracy: 0.7950 - 527ms/epoch - 10ms/step
Epoch 770/1500
51/51 - 1s - loss: 0.0799 - categorical_accuracy: 0.9687 - val_loss: 1.9072 - val_categorical_accuracy: 0.7925 - 510ms/epoch - 10ms/step
Epoch 771/1500
51/51 - 1s - loss: 0.0752 - categorical_accuracy: 0.9714 - val_loss: 1.9195 - val_categorical_accuracy: 0.7883 - 540ms/epoch - 11ms/step
Epoch 772/1500
51/51 - 1s - loss: 0.0914 - categorical_accuracy: 0.9658 - val_loss: 1.9686 - val_categorical_accuracy: 0.7998 - 534ms/epoch - 10ms/step
Epoch 773/1500
51/51 - 1s - loss: 0.0858 - categorical_accuracy: 0.9677 - val_loss: 1.9772 - val_categorical_accuracy: 0.7830 - 518ms/epoch - 10ms/step
Epoch 774/1500
51/51 - 0s - loss: 0.1845 - categorical_accuracy: 0.9468 - val_loss: 1.7173 - val_categorical_accuracy: 0.7644 - 491ms/epoch - 10ms/step
Epoch 775/1500
51/51 - 1s - loss: 0.1226 - categorical_accuracy: 0.9551 - val_loss: 1.9505 - val_categorical_accuracy: 0.7996 - 527ms/epoch - 10ms/step
Epoch 776/1500
51/51 - 0s - loss: 0.1033 - categorical_accuracy: 0.9610 - val_loss: 1.8235 - val_categorical_accuracy: 0.7946 - 490ms/epoch - 10ms/step
Epoch 777/1500
51/51 - 1s - loss: 0.0818 - categorical_accuracy: 0.9689 - val_loss: 1.9413 - val_categorical_accuracy: 0.7929 - 522ms/epoch - 10ms/step
Epoch 778/1500
51/51 - 0s - loss: 0.0852 - categorical_accuracy: 0.9676 - val_loss: 1.9164 - val_categorical_accuracy: 0.7927 - 488ms/epoch - 10ms/step
Epoch 779/1500
51/51 - 1s - loss: 0.0843 - categorical_accuracy: 0.9678 - val_loss: 1.9087 - val_categorical_accuracy: 0.7880 - 539ms/epoch - 11ms/step
Epoch 780/1500
51/51 - 0s - loss: 0.0787 - categorical_accuracy: 0.9696 - val_loss: 1.9526 - val_categorical_accuracy: 0.7925 - 493ms/epoch - 10ms/step
Epoch 781/1500
51/51 - 1s - loss: 0.0835 - categorical_accuracy: 0.9685 - val_loss: 1.9484 - val_categorical_accuracy: 0.7858 - 537ms/epoch - 11ms/step
Epoch 782/1500
51/51 - 1s - loss: 0.0827 - categorical_accuracy: 0.9690 - val_loss: 1.9554 - val_categorical_accuracy: 0.7878 - 509ms/epoch - 10ms/step
Epoch 783/1500
51/51 - 1s - loss: 0.0785 - categorical_accuracy: 0.9708 - val_loss: 1.9302 - val_categorical_accuracy: 0.7960 - 515ms/epoch - 10ms/step
Epoch 784/1500
51/51 - 1s - loss: 0.0758 - categorical_accuracy: 0.9704 - val_loss: 2.0029 - val_categorical_accuracy: 0.7949 - 506ms/epoch - 10ms/step
Epoch 785/1500
51/51 - 1s - loss: 0.0789 - categorical_accuracy: 0.9701 - val_loss: 1.9106 - val_categorical_accuracy: 0.7882 - 548ms/epoch - 11ms/step
Epoch 786/1500
51/51 - 1s - loss: 0.0734 - categorical_accuracy: 0.9723 - val_loss: 2.0147 - val_categorical_accuracy: 0.7897 - 518ms/epoch - 10ms/step
Epoch 787/1500
51/51 - 1s - loss: 0.0828 - categorical_accuracy: 0.9680 - val_loss: 1.9658 - val_categorical_accuracy: 0.7792 - 566ms/epoch - 11ms/step
Epoch 788/1500
51/51 - 0s - loss: 0.0849 - categorical_accuracy: 0.9675 - val_loss: 1.9811 - val_categorical_accuracy: 0.7751 - 486ms/epoch - 10ms/step
Epoch 789/1500
51/51 - 1s - loss: 0.2166 - categorical_accuracy: 0.9368 - val_loss: 1.8026 - val_categorical_accuracy: 0.7845 - 556ms/epoch - 11ms/step
Epoch 790/1500
51/51 - 1s - loss: 0.0896 - categorical_accuracy: 0.9656 - val_loss: 1.9026 - val_categorical_accuracy: 0.7933 - 540ms/epoch - 11ms/step
Epoch 791/1500
51/51 - 1s - loss: 0.0824 - categorical_accuracy: 0.9673 - val_loss: 1.9409 - val_categorical_accuracy: 0.7885 - 547ms/epoch - 11ms/step
Epoch 792/1500
51/51 - 1s - loss: 0.2503 - categorical_accuracy: 0.9284 - val_loss: 1.7010 - val_categorical_accuracy: 0.7961 - 539ms/epoch - 11ms/step
Epoch 793/1500
51/51 - 1s - loss: 0.0827 - categorical_accuracy: 0.9687 - val_loss: 1.7779 - val_categorical_accuracy: 0.7943 - 520ms/epoch - 10ms/step
Epoch 794/1500
51/51 - 1s - loss: 0.0734 - categorical_accuracy: 0.9729 - val_loss: 1.8333 - val_categorical_accuracy: 0.7948 - 539ms/epoch - 11ms/step
Epoch 795/1500
51/51 - 1s - loss: 0.0736 - categorical_accuracy: 0.9731 - val_loss: 1.8984 - val_categorical_accuracy: 0.7980 - 549ms/epoch - 11ms/step
Epoch 796/1500
51/51 - 1s - loss: 0.0736 - categorical_accuracy: 0.9719 - val_loss: 1.9230 - val_categorical_accuracy: 0.7965 - 559ms/epoch - 11ms/step
Epoch 797/1500
51/51 - 1s - loss: 0.0800 - categorical_accuracy: 0.9690 - val_loss: 1.9123 - val_categorical_accuracy: 0.7949 - 519ms/epoch - 10ms/step
Epoch 798/1500
51/51 - 1s - loss: 0.0761 - categorical_accuracy: 0.9708 - val_loss: 1.9752 - val_categorical_accuracy: 0.7901 - 531ms/epoch - 10ms/step
Epoch 799/1500
51/51 - 1s - loss: 0.0734 - categorical_accuracy: 0.9717 - val_loss: 1.9660 - val_categorical_accuracy: 0.7988 - 537ms/epoch - 11ms/step
Epoch 800/1500
51/51 - 1s - loss: 0.0701 - categorical_accuracy: 0.9733 - val_loss: 1.9270 - val_categorical_accuracy: 0.7916 - 540ms/epoch - 11ms/step
Epoch 801/1500
51/51 - 1s - loss: 0.0747 - categorical_accuracy: 0.9708 - val_loss: 2.0006 - val_categorical_accuracy: 0.7941 - 539ms/epoch - 11ms/step
Epoch 802/1500
51/51 - 1s - loss: 0.0765 - categorical_accuracy: 0.9695 - val_loss: 2.0262 - val_categorical_accuracy: 0.7986 - 530ms/epoch - 10ms/step
Epoch 803/1500
51/51 - 1s - loss: 0.0746 - categorical_accuracy: 0.9707 - val_loss: 2.0196 - val_categorical_accuracy: 0.7879 - 530ms/epoch - 10ms/step
Epoch 804/1500
51/51 - 1s - loss: 0.0752 - categorical_accuracy: 0.9712 - val_loss: 1.9870 - val_categorical_accuracy: 0.7897 - 522ms/epoch - 10ms/step
Epoch 805/1500
51/51 - 1s - loss: 0.0742 - categorical_accuracy: 0.9712 - val_loss: 2.0626 - val_categorical_accuracy: 0.7755 - 541ms/epoch - 11ms/step
Epoch 806/1500
51/51 - 1s - loss: 0.0847 - categorical_accuracy: 0.9676 - val_loss: 2.0242 - val_categorical_accuracy: 0.7918 - 524ms/epoch - 10ms/step
Epoch 807/1500
51/51 - 1s - loss: 0.1050 - categorical_accuracy: 0.9631 - val_loss: 2.0490 - val_categorical_accuracy: 0.7628 - 542ms/epoch - 11ms/step
Epoch 808/1500
51/51 - 1s - loss: 0.2841 - categorical_accuracy: 0.9216 - val_loss: 1.7305 - val_categorical_accuracy: 0.7986 - 533ms/epoch - 10ms/step
Epoch 809/1500
51/51 - 1s - loss: 0.0834 - categorical_accuracy: 0.9686 - val_loss: 1.8465 - val_categorical_accuracy: 0.7951 - 533ms/epoch - 10ms/step
Epoch 810/1500
51/51 - 1s - loss: 0.0755 - categorical_accuracy: 0.9716 - val_loss: 1.8358 - val_categorical_accuracy: 0.7964 - 548ms/epoch - 11ms/step
Epoch 811/1500
51/51 - 1s - loss: 0.0737 - categorical_accuracy: 0.9713 - val_loss: 1.9233 - val_categorical_accuracy: 0.7961 - 550ms/epoch - 11ms/step
Epoch 812/1500
51/51 - 1s - loss: 0.0772 - categorical_accuracy: 0.9709 - val_loss: 1.9569 - val_categorical_accuracy: 0.7921 - 514ms/epoch - 10ms/step
Epoch 813/1500
51/51 - 1s - loss: 0.0771 - categorical_accuracy: 0.9700 - val_loss: 1.9299 - val_categorical_accuracy: 0.7878 - 548ms/epoch - 11ms/step
Epoch 814/1500
51/51 - 1s - loss: 0.0751 - categorical_accuracy: 0.9708 - val_loss: 1.9614 - val_categorical_accuracy: 0.7920 - 526ms/epoch - 10ms/step
Epoch 815/1500
51/51 - 1s - loss: 0.0741 - categorical_accuracy: 0.9710 - val_loss: 1.9814 - val_categorical_accuracy: 0.7862 - 541ms/epoch - 11ms/step
Epoch 816/1500
51/51 - 1s - loss: 0.0746 - categorical_accuracy: 0.9704 - val_loss: 2.0036 - val_categorical_accuracy: 0.7938 - 537ms/epoch - 11ms/step
Epoch 817/1500
51/51 - 1s - loss: 0.0749 - categorical_accuracy: 0.9710 - val_loss: 1.9629 - val_categorical_accuracy: 0.7849 - 539ms/epoch - 11ms/step
Epoch 818/1500
51/51 - 1s - loss: 0.0802 - categorical_accuracy: 0.9688 - val_loss: 2.0779 - val_categorical_accuracy: 0.7908 - 540ms/epoch - 11ms/step
Epoch 819/1500
51/51 - 1s - loss: 0.0938 - categorical_accuracy: 0.9639 - val_loss: 2.0056 - val_categorical_accuracy: 0.7941 - 522ms/epoch - 10ms/step
Epoch 820/1500
51/51 - 1s - loss: 0.0795 - categorical_accuracy: 0.9696 - val_loss: 2.0647 - val_categorical_accuracy: 0.7950 - 555ms/epoch - 11ms/step
Epoch 821/1500
51/51 - 1s - loss: 0.2531 - categorical_accuracy: 0.9339 - val_loss: 1.5061 - val_categorical_accuracy: 0.7856 - 510ms/epoch - 10ms/step
Epoch 822/1500
51/51 - 1s - loss: 0.1224 - categorical_accuracy: 0.9537 - val_loss: 1.7647 - val_categorical_accuracy: 0.7860 - 534ms/epoch - 10ms/step
Epoch 823/1500
51/51 - 1s - loss: 0.0842 - categorical_accuracy: 0.9675 - val_loss: 1.8028 - val_categorical_accuracy: 0.7963 - 527ms/epoch - 10ms/step
Epoch 824/1500
51/51 - 1s - loss: 0.0727 - categorical_accuracy: 0.9719 - val_loss: 1.9264 - val_categorical_accuracy: 0.7966 - 552ms/epoch - 11ms/step
Epoch 825/1500
51/51 - 1s - loss: 0.0779 - categorical_accuracy: 0.9700 - val_loss: 1.8956 - val_categorical_accuracy: 0.7944 - 540ms/epoch - 11ms/step
Epoch 826/1500
51/51 - 1s - loss: 0.0744 - categorical_accuracy: 0.9715 - val_loss: 1.9369 - val_categorical_accuracy: 0.7886 - 553ms/epoch - 11ms/step
Epoch 827/1500
51/51 - 1s - loss: 0.0747 - categorical_accuracy: 0.9706 - val_loss: 1.9350 - val_categorical_accuracy: 0.7918 - 524ms/epoch - 10ms/step
Epoch 828/1500
51/51 - 1s - loss: 0.0739 - categorical_accuracy: 0.9723 - val_loss: 1.9845 - val_categorical_accuracy: 0.7933 - 573ms/epoch - 11ms/step
Epoch 829/1500
51/51 - 1s - loss: 0.0745 - categorical_accuracy: 0.9703 - val_loss: 1.9802 - val_categorical_accuracy: 0.7933 - 538ms/epoch - 11ms/step
Epoch 830/1500
51/51 - 1s - loss: 0.0818 - categorical_accuracy: 0.9680 - val_loss: 2.0072 - val_categorical_accuracy: 0.7953 - 559ms/epoch - 11ms/step
Epoch 831/1500
51/51 - 1s - loss: 0.0774 - categorical_accuracy: 0.9699 - val_loss: 1.9811 - val_categorical_accuracy: 0.7944 - 573ms/epoch - 11ms/step
Epoch 832/1500
51/51 - 1s - loss: 0.0886 - categorical_accuracy: 0.9665 - val_loss: 1.9709 - val_categorical_accuracy: 0.7896 - 509ms/epoch - 10ms/step
Epoch 833/1500
51/51 - 1s - loss: 0.0898 - categorical_accuracy: 0.9663 - val_loss: 1.9770 - val_categorical_accuracy: 0.7889 - 529ms/epoch - 10ms/step
Epoch 834/1500
51/51 - 0s - loss: 0.0781 - categorical_accuracy: 0.9708 - val_loss: 2.0646 - val_categorical_accuracy: 0.7933 - 487ms/epoch - 10ms/step
Epoch 835/1500
51/51 - 1s - loss: 0.0857 - categorical_accuracy: 0.9666 - val_loss: 1.9782 - val_categorical_accuracy: 0.7853 - 536ms/epoch - 11ms/step
Epoch 836/1500
51/51 - 1s - loss: 0.0818 - categorical_accuracy: 0.9677 - val_loss: 2.0143 - val_categorical_accuracy: 0.7969 - 506ms/epoch - 10ms/step
Epoch 837/1500
51/51 - 1s - loss: 0.0790 - categorical_accuracy: 0.9705 - val_loss: 2.0900 - val_categorical_accuracy: 0.7971 - 555ms/epoch - 11ms/step
Epoch 838/1500
51/51 - 1s - loss: 0.2545 - categorical_accuracy: 0.9338 - val_loss: 1.3618 - val_categorical_accuracy: 0.7751 - 509ms/epoch - 10ms/step
Epoch 839/1500
51/51 - 1s - loss: 0.1226 - categorical_accuracy: 0.9528 - val_loss: 1.8055 - val_categorical_accuracy: 0.7891 - 537ms/epoch - 11ms/step
Epoch 840/1500
51/51 - 1s - loss: 0.0801 - categorical_accuracy: 0.9705 - val_loss: 1.8497 - val_categorical_accuracy: 0.7971 - 514ms/epoch - 10ms/step
Epoch 841/1500
51/51 - 1s - loss: 0.0725 - categorical_accuracy: 0.9726 - val_loss: 1.9686 - val_categorical_accuracy: 0.7914 - 525ms/epoch - 10ms/step
Epoch 842/1500
51/51 - 1s - loss: 0.0752 - categorical_accuracy: 0.9709 - val_loss: 1.9402 - val_categorical_accuracy: 0.7945 - 524ms/epoch - 10ms/step
Epoch 843/1500
51/51 - 1s - loss: 0.0709 - categorical_accuracy: 0.9719 - val_loss: 2.0112 - val_categorical_accuracy: 0.7911 - 525ms/epoch - 10ms/step
Epoch 844/1500
51/51 - 1s - loss: 0.0733 - categorical_accuracy: 0.9717 - val_loss: 1.9586 - val_categorical_accuracy: 0.7843 - 506ms/epoch - 10ms/step
Epoch 845/1500
51/51 - 1s - loss: 0.0735 - categorical_accuracy: 0.9721 - val_loss: 2.0036 - val_categorical_accuracy: 0.7959 - 523ms/epoch - 10ms/step
Epoch 846/1500
51/51 - 1s - loss: 0.0686 - categorical_accuracy: 0.9734 - val_loss: 2.0452 - val_categorical_accuracy: 0.7937 - 518ms/epoch - 10ms/step
Epoch 847/1500
51/51 - 1s - loss: 0.0715 - categorical_accuracy: 0.9714 - val_loss: 1.9878 - val_categorical_accuracy: 0.7834 - 547ms/epoch - 11ms/step
Epoch 848/1500
51/51 - 1s - loss: 0.0691 - categorical_accuracy: 0.9735 - val_loss: 2.0100 - val_categorical_accuracy: 0.7921 - 558ms/epoch - 11ms/step
Epoch 849/1500
51/51 - 1s - loss: 0.0719 - categorical_accuracy: 0.9718 - val_loss: 2.0110 - val_categorical_accuracy: 0.7912 - 510ms/epoch - 10ms/step
Epoch 850/1500
51/51 - 1s - loss: 0.0771 - categorical_accuracy: 0.9702 - val_loss: 2.0540 - val_categorical_accuracy: 0.7839 - 503ms/epoch - 10ms/step
Epoch 851/1500
51/51 - 0s - loss: 0.0730 - categorical_accuracy: 0.9716 - val_loss: 2.0517 - val_categorical_accuracy: 0.7944 - 498ms/epoch - 10ms/step
Epoch 852/1500
51/51 - 1s - loss: 0.0700 - categorical_accuracy: 0.9723 - val_loss: 2.0612 - val_categorical_accuracy: 0.7947 - 509ms/epoch - 10ms/step
Epoch 853/1500
51/51 - 0s - loss: 0.0698 - categorical_accuracy: 0.9726 - val_loss: 2.0812 - val_categorical_accuracy: 0.7923 - 488ms/epoch - 10ms/step
Epoch 854/1500
51/51 - 1s - loss: 0.0798 - categorical_accuracy: 0.9691 - val_loss: 2.0278 - val_categorical_accuracy: 0.7797 - 520ms/epoch - 10ms/step
Epoch 855/1500
51/51 - 1s - loss: 0.0733 - categorical_accuracy: 0.9707 - val_loss: 2.1957 - val_categorical_accuracy: 0.7948 - 502ms/epoch - 10ms/step
Epoch 856/1500
51/51 - 1s - loss: 0.0794 - categorical_accuracy: 0.9695 - val_loss: 2.1640 - val_categorical_accuracy: 0.7867 - 536ms/epoch - 11ms/step
Epoch 857/1500
51/51 - 1s - loss: 0.0758 - categorical_accuracy: 0.9714 - val_loss: 2.0663 - val_categorical_accuracy: 0.7917 - 538ms/epoch - 11ms/step
Epoch 858/1500
51/51 - 1s - loss: 0.0746 - categorical_accuracy: 0.9716 - val_loss: 2.0834 - val_categorical_accuracy: 0.7899 - 576ms/epoch - 11ms/step
Epoch 859/1500
51/51 - 1s - loss: 0.2459 - categorical_accuracy: 0.9263 - val_loss: 1.8524 - val_categorical_accuracy: 0.7756 - 542ms/epoch - 11ms/step
Epoch 860/1500
51/51 - 1s - loss: 0.0959 - categorical_accuracy: 0.9631 - val_loss: 1.9159 - val_categorical_accuracy: 0.7846 - 557ms/epoch - 11ms/step
Epoch 861/1500
51/51 - 1s - loss: 0.0762 - categorical_accuracy: 0.9701 - val_loss: 1.9631 - val_categorical_accuracy: 0.7973 - 553ms/epoch - 11ms/step
Epoch 862/1500
51/51 - 1s - loss: 0.0756 - categorical_accuracy: 0.9705 - val_loss: 2.0261 - val_categorical_accuracy: 0.7722 - 519ms/epoch - 10ms/step
Epoch 863/1500
51/51 - 1s - loss: 0.0892 - categorical_accuracy: 0.9659 - val_loss: 2.0247 - val_categorical_accuracy: 0.7843 - 553ms/epoch - 11ms/step
Epoch 864/1500
51/51 - 1s - loss: 0.0750 - categorical_accuracy: 0.9704 - val_loss: 2.0401 - val_categorical_accuracy: 0.7949 - 552ms/epoch - 11ms/step
Epoch 865/1500
51/51 - 1s - loss: 0.0846 - categorical_accuracy: 0.9665 - val_loss: 2.0275 - val_categorical_accuracy: 0.7934 - 561ms/epoch - 11ms/step
Epoch 866/1500
51/51 - 1s - loss: 0.0739 - categorical_accuracy: 0.9702 - val_loss: 2.0768 - val_categorical_accuracy: 0.7716 - 593ms/epoch - 12ms/step
Epoch 867/1500
51/51 - 1s - loss: 0.0851 - categorical_accuracy: 0.9666 - val_loss: 2.0818 - val_categorical_accuracy: 0.7912 - 557ms/epoch - 11ms/step
Epoch 868/1500
51/51 - 1s - loss: 0.0862 - categorical_accuracy: 0.9681 - val_loss: 2.0602 - val_categorical_accuracy: 0.7899 - 508ms/epoch - 10ms/step
Epoch 869/1500
51/51 - 1s - loss: 0.0727 - categorical_accuracy: 0.9721 - val_loss: 2.0627 - val_categorical_accuracy: 0.7931 - 555ms/epoch - 11ms/step
Epoch 870/1500
51/51 - 1s - loss: 0.0776 - categorical_accuracy: 0.9705 - val_loss: 2.0348 - val_categorical_accuracy: 0.7902 - 544ms/epoch - 11ms/step
Epoch 871/1500
51/51 - 1s - loss: 0.0686 - categorical_accuracy: 0.9728 - val_loss: 2.0834 - val_categorical_accuracy: 0.7928 - 540ms/epoch - 11ms/step
Epoch 872/1500
51/51 - 1s - loss: 0.0790 - categorical_accuracy: 0.9702 - val_loss: 2.1705 - val_categorical_accuracy: 0.7909 - 559ms/epoch - 11ms/step
Epoch 873/1500
51/51 - 1s - loss: 0.0832 - categorical_accuracy: 0.9689 - val_loss: 2.0344 - val_categorical_accuracy: 0.7941 - 569ms/epoch - 11ms/step
Epoch 874/1500
51/51 - 1s - loss: 0.0723 - categorical_accuracy: 0.9724 - val_loss: 2.0808 - val_categorical_accuracy: 0.7893 - 574ms/epoch - 11ms/step
Epoch 875/1500
51/51 - 1s - loss: 0.0758 - categorical_accuracy: 0.9711 - val_loss: 2.0727 - val_categorical_accuracy: 0.7942 - 525ms/epoch - 10ms/step
Epoch 876/1500
51/51 - 1s - loss: 0.0730 - categorical_accuracy: 0.9715 - val_loss: 2.0976 - val_categorical_accuracy: 0.7920 - 562ms/epoch - 11ms/step
Epoch 877/1500
51/51 - 1s - loss: 0.0777 - categorical_accuracy: 0.9699 - val_loss: 2.0584 - val_categorical_accuracy: 0.7890 - 535ms/epoch - 10ms/step
Epoch 878/1500
51/51 - 1s - loss: 0.0715 - categorical_accuracy: 0.9720 - val_loss: 2.0951 - val_categorical_accuracy: 0.7923 - 587ms/epoch - 12ms/step
Epoch 879/1500
51/51 - 1s - loss: 0.0699 - categorical_accuracy: 0.9729 - val_loss: 2.2245 - val_categorical_accuracy: 0.7984 - 555ms/epoch - 11ms/step
Epoch 880/1500
51/51 - 1s - loss: 0.0827 - categorical_accuracy: 0.9682 - val_loss: 2.0915 - val_categorical_accuracy: 0.7887 - 546ms/epoch - 11ms/step
Epoch 881/1500
51/51 - 1s - loss: 0.0761 - categorical_accuracy: 0.9705 - val_loss: 2.1131 - val_categorical_accuracy: 0.7845 - 564ms/epoch - 11ms/step
Epoch 882/1500
51/51 - 1s - loss: 0.0846 - categorical_accuracy: 0.9679 - val_loss: 2.1319 - val_categorical_accuracy: 0.7892 - 544ms/epoch - 11ms/step
Epoch 883/1500
51/51 - 1s - loss: 0.0776 - categorical_accuracy: 0.9696 - val_loss: 2.1299 - val_categorical_accuracy: 0.7939 - 544ms/epoch - 11ms/step
Epoch 884/1500
51/51 - 1s - loss: 0.2398 - categorical_accuracy: 0.9366 - val_loss: 1.7808 - val_categorical_accuracy: 0.7917 - 567ms/epoch - 11ms/step
Epoch 885/1500
51/51 - 1s - loss: 0.0964 - categorical_accuracy: 0.9636 - val_loss: 1.9759 - val_categorical_accuracy: 0.7939 - 556ms/epoch - 11ms/step
Epoch 886/1500
51/51 - 1s - loss: 0.0759 - categorical_accuracy: 0.9709 - val_loss: 1.9863 - val_categorical_accuracy: 0.7845 - 542ms/epoch - 11ms/step
Epoch 887/1500
51/51 - 1s - loss: 0.0751 - categorical_accuracy: 0.9723 - val_loss: 2.0116 - val_categorical_accuracy: 0.7896 - 552ms/epoch - 11ms/step
Epoch 888/1500
51/51 - 1s - loss: 0.0698 - categorical_accuracy: 0.9737 - val_loss: 2.0391 - val_categorical_accuracy: 0.7915 - 538ms/epoch - 11ms/step
Epoch 889/1500
51/51 - 1s - loss: 0.0727 - categorical_accuracy: 0.9726 - val_loss: 2.0886 - val_categorical_accuracy: 0.7828 - 558ms/epoch - 11ms/step
Epoch 890/1500
51/51 - 1s - loss: 0.0684 - categorical_accuracy: 0.9738 - val_loss: 2.0589 - val_categorical_accuracy: 0.7887 - 534ms/epoch - 10ms/step
Epoch 891/1500
51/51 - 1s - loss: 0.0742 - categorical_accuracy: 0.9710 - val_loss: 2.1291 - val_categorical_accuracy: 0.7954 - 538ms/epoch - 11ms/step
Epoch 892/1500
51/51 - 1s - loss: 0.0715 - categorical_accuracy: 0.9719 - val_loss: 2.1041 - val_categorical_accuracy: 0.7867 - 554ms/epoch - 11ms/step
Epoch 893/1500
51/51 - 1s - loss: 0.0694 - categorical_accuracy: 0.9726 - val_loss: 2.0873 - val_categorical_accuracy: 0.7861 - 509ms/epoch - 10ms/step
Epoch 894/1500
51/51 - 1s - loss: 0.0777 - categorical_accuracy: 0.9697 - val_loss: 2.0891 - val_categorical_accuracy: 0.7927 - 534ms/epoch - 10ms/step
Epoch 895/1500
51/51 - 1s - loss: 0.0736 - categorical_accuracy: 0.9719 - val_loss: 2.2185 - val_categorical_accuracy: 0.7786 - 509ms/epoch - 10ms/step
Epoch 896/1500
51/51 - 1s - loss: 0.2826 - categorical_accuracy: 0.9246 - val_loss: 1.8636 - val_categorical_accuracy: 0.7893 - 505ms/epoch - 10ms/step
Epoch 897/1500
51/51 - 0s - loss: 0.0816 - categorical_accuracy: 0.9688 - val_loss: 2.5226 - val_categorical_accuracy: 0.7854 - 492ms/epoch - 10ms/step
Epoch 898/1500
51/51 - 1s - loss: 0.2868 - categorical_accuracy: 0.9279 - val_loss: 1.7074 - val_categorical_accuracy: 0.7887 - 521ms/epoch - 10ms/step
Epoch 899/1500
51/51 - 0s - loss: 0.0747 - categorical_accuracy: 0.9724 - val_loss: 1.8086 - val_categorical_accuracy: 0.7938 - 493ms/epoch - 10ms/step
Epoch 900/1500
51/51 - 1s - loss: 0.0668 - categorical_accuracy: 0.9745 - val_loss: 1.8787 - val_categorical_accuracy: 0.7901 - 520ms/epoch - 10ms/step
Epoch 901/1500
51/51 - 0s - loss: 0.0691 - categorical_accuracy: 0.9737 - val_loss: 1.9572 - val_categorical_accuracy: 0.7938 - 491ms/epoch - 10ms/step
Epoch 902/1500
51/51 - 1s - loss: 0.0644 - categorical_accuracy: 0.9755 - val_loss: 1.9651 - val_categorical_accuracy: 0.7932 - 545ms/epoch - 11ms/step
Epoch 903/1500
51/51 - 1s - loss: 0.0658 - categorical_accuracy: 0.9745 - val_loss: 1.9780 - val_categorical_accuracy: 0.7928 - 502ms/epoch - 10ms/step
Epoch 904/1500
51/51 - 1s - loss: 0.0650 - categorical_accuracy: 0.9741 - val_loss: 2.0073 - val_categorical_accuracy: 0.7978 - 525ms/epoch - 10ms/step
Epoch 905/1500
51/51 - 0s - loss: 0.0676 - categorical_accuracy: 0.9739 - val_loss: 2.0355 - val_categorical_accuracy: 0.7892 - 486ms/epoch - 10ms/step
Epoch 906/1500
51/51 - 1s - loss: 0.0673 - categorical_accuracy: 0.9732 - val_loss: 2.0791 - val_categorical_accuracy: 0.7936 - 508ms/epoch - 10ms/step
Epoch 907/1500
51/51 - 0s - loss: 0.0691 - categorical_accuracy: 0.9740 - val_loss: 2.0635 - val_categorical_accuracy: 0.7864 - 492ms/epoch - 10ms/step
Epoch 908/1500
51/51 - 1s - loss: 0.0808 - categorical_accuracy: 0.9700 - val_loss: 1.9980 - val_categorical_accuracy: 0.7898 - 507ms/epoch - 10ms/step
Epoch 909/1500
51/51 - 0s - loss: 0.2259 - categorical_accuracy: 0.9311 - val_loss: 1.8412 - val_categorical_accuracy: 0.7894 - 478ms/epoch - 9ms/step
Epoch 910/1500
51/51 - 1s - loss: 0.0742 - categorical_accuracy: 0.9720 - val_loss: 1.9670 - val_categorical_accuracy: 0.7942 - 503ms/epoch - 10ms/step
Epoch 911/1500
51/51 - 1s - loss: 0.0692 - categorical_accuracy: 0.9739 - val_loss: 1.9458 - val_categorical_accuracy: 0.7874 - 506ms/epoch - 10ms/step
Epoch 912/1500
51/51 - 1s - loss: 0.0728 - categorical_accuracy: 0.9712 - val_loss: 2.0761 - val_categorical_accuracy: 0.7964 - 538ms/epoch - 11ms/step
Epoch 913/1500
51/51 - 1s - loss: 0.0688 - categorical_accuracy: 0.9737 - val_loss: 2.0078 - val_categorical_accuracy: 0.7937 - 510ms/epoch - 10ms/step
Epoch 914/1500
51/51 - 1s - loss: 0.0706 - categorical_accuracy: 0.9734 - val_loss: 2.0494 - val_categorical_accuracy: 0.7920 - 524ms/epoch - 10ms/step
Epoch 915/1500
51/51 - 1s - loss: 0.0677 - categorical_accuracy: 0.9731 - val_loss: 2.0632 - val_categorical_accuracy: 0.7939 - 500ms/epoch - 10ms/step
Epoch 916/1500
51/51 - 1s - loss: 0.0675 - categorical_accuracy: 0.9735 - val_loss: 2.0313 - val_categorical_accuracy: 0.7893 - 508ms/epoch - 10ms/step
Epoch 917/1500
51/51 - 1s - loss: 0.0699 - categorical_accuracy: 0.9729 - val_loss: 2.0859 - val_categorical_accuracy: 0.7864 - 522ms/epoch - 10ms/step
Epoch 918/1500
51/51 - 1s - loss: 0.0680 - categorical_accuracy: 0.9738 - val_loss: 2.0750 - val_categorical_accuracy: 0.7938 - 517ms/epoch - 10ms/step
Epoch 919/1500
51/51 - 1s - loss: 0.0685 - categorical_accuracy: 0.9734 - val_loss: 2.0890 - val_categorical_accuracy: 0.7934 - 509ms/epoch - 10ms/step
Epoch 920/1500
51/51 - 1s - loss: 0.0644 - categorical_accuracy: 0.9754 - val_loss: 2.0818 - val_categorical_accuracy: 0.7911 - 515ms/epoch - 10ms/step
Epoch 921/1500
51/51 - 1s - loss: 0.0722 - categorical_accuracy: 0.9726 - val_loss: 2.1108 - val_categorical_accuracy: 0.7818 - 517ms/epoch - 10ms/step
Epoch 922/1500
51/51 - 1s - loss: 0.0713 - categorical_accuracy: 0.9718 - val_loss: 2.1110 - val_categorical_accuracy: 0.7849 - 549ms/epoch - 11ms/step
Epoch 923/1500
51/51 - 1s - loss: 0.0963 - categorical_accuracy: 0.9646 - val_loss: 2.1152 - val_categorical_accuracy: 0.7892 - 535ms/epoch - 10ms/step
Epoch 924/1500
51/51 - 1s - loss: 0.2547 - categorical_accuracy: 0.9268 - val_loss: 1.8447 - val_categorical_accuracy: 0.7968 - 520ms/epoch - 10ms/step
Epoch 925/1500
51/51 - 1s - loss: 0.0762 - categorical_accuracy: 0.9710 - val_loss: 1.9032 - val_categorical_accuracy: 0.7890 - 539ms/epoch - 11ms/step
Epoch 926/1500
51/51 - 1s - loss: 0.0705 - categorical_accuracy: 0.9732 - val_loss: 1.9732 - val_categorical_accuracy: 0.7930 - 507ms/epoch - 10ms/step
Epoch 927/1500
51/51 - 1s - loss: 0.0703 - categorical_accuracy: 0.9732 - val_loss: 2.0105 - val_categorical_accuracy: 0.7964 - 540ms/epoch - 11ms/step
Epoch 928/1500
51/51 - 1s - loss: 0.0711 - categorical_accuracy: 0.9723 - val_loss: 2.0109 - val_categorical_accuracy: 0.7909 - 509ms/epoch - 10ms/step
Epoch 929/1500
51/51 - 1s - loss: 0.0692 - categorical_accuracy: 0.9728 - val_loss: 2.0836 - val_categorical_accuracy: 0.7864 - 538ms/epoch - 11ms/step
Epoch 930/1500
51/51 - 1s - loss: 0.0705 - categorical_accuracy: 0.9732 - val_loss: 2.1134 - val_categorical_accuracy: 0.7956 - 520ms/epoch - 10ms/step
Epoch 931/1500
51/51 - 1s - loss: 0.0689 - categorical_accuracy: 0.9733 - val_loss: 2.0814 - val_categorical_accuracy: 0.8001 - 523ms/epoch - 10ms/step
Epoch 932/1500
51/51 - 0s - loss: 0.0709 - categorical_accuracy: 0.9726 - val_loss: 2.0425 - val_categorical_accuracy: 0.7892 - 493ms/epoch - 10ms/step
Epoch 933/1500
51/51 - 1s - loss: 0.0685 - categorical_accuracy: 0.9729 - val_loss: 2.0419 - val_categorical_accuracy: 0.7905 - 504ms/epoch - 10ms/step
Epoch 934/1500
51/51 - 0s - loss: 0.0687 - categorical_accuracy: 0.9734 - val_loss: 2.0940 - val_categorical_accuracy: 0.7906 - 493ms/epoch - 10ms/step
Epoch 935/1500
51/51 - 1s - loss: 0.0673 - categorical_accuracy: 0.9734 - val_loss: 2.0679 - val_categorical_accuracy: 0.7867 - 538ms/epoch - 11ms/step
Epoch 936/1500
51/51 - 1s - loss: 0.0794 - categorical_accuracy: 0.9692 - val_loss: 2.1071 - val_categorical_accuracy: 0.7879 - 510ms/epoch - 10ms/step
Epoch 937/1500
51/51 - 1s - loss: 0.0888 - categorical_accuracy: 0.9676 - val_loss: 2.1082 - val_categorical_accuracy: 0.7898 - 522ms/epoch - 10ms/step
Epoch 938/1500
51/51 - 1s - loss: 0.0818 - categorical_accuracy: 0.9677 - val_loss: 2.0753 - val_categorical_accuracy: 0.7908 - 522ms/epoch - 10ms/step
Epoch 939/1500
51/51 - 1s - loss: 0.0717 - categorical_accuracy: 0.9719 - val_loss: 2.1288 - val_categorical_accuracy: 0.7825 - 530ms/epoch - 10ms/step
Epoch 940/1500
51/51 - 1s - loss: 0.0733 - categorical_accuracy: 0.9726 - val_loss: 2.1430 - val_categorical_accuracy: 0.7946 - 505ms/epoch - 10ms/step
Epoch 941/1500
51/51 - 1s - loss: 0.0685 - categorical_accuracy: 0.9734 - val_loss: 2.1364 - val_categorical_accuracy: 0.7723 - 535ms/epoch - 10ms/step
Epoch 942/1500
51/51 - 1s - loss: 0.0707 - categorical_accuracy: 0.9725 - val_loss: 2.1644 - val_categorical_accuracy: 0.7844 - 510ms/epoch - 10ms/step
Epoch 943/1500
51/51 - 1s - loss: 0.0750 - categorical_accuracy: 0.9710 - val_loss: 2.1431 - val_categorical_accuracy: 0.7869 - 504ms/epoch - 10ms/step
Epoch 944/1500
51/51 - 1s - loss: 0.0743 - categorical_accuracy: 0.9712 - val_loss: 2.1265 - val_categorical_accuracy: 0.7892 - 507ms/epoch - 10ms/step
Epoch 945/1500
51/51 - 0s - loss: 0.0662 - categorical_accuracy: 0.9743 - val_loss: 2.1939 - val_categorical_accuracy: 0.7880 - 486ms/epoch - 10ms/step
Epoch 946/1500
51/51 - 0s - loss: 0.0662 - categorical_accuracy: 0.9743 - val_loss: 2.1920 - val_categorical_accuracy: 0.7919 - 499ms/epoch - 10ms/step
Epoch 947/1500
51/51 - 1s - loss: 0.0790 - categorical_accuracy: 0.9702 - val_loss: 2.8988 - val_categorical_accuracy: 0.6590 - 507ms/epoch - 10ms/step
Epoch 948/1500
51/51 - 1s - loss: 0.2558 - categorical_accuracy: 0.9292 - val_loss: 1.9606 - val_categorical_accuracy: 0.7730 - 516ms/epoch - 10ms/step
Epoch 949/1500
51/51 - 0s - loss: 0.0788 - categorical_accuracy: 0.9695 - val_loss: 1.9891 - val_categorical_accuracy: 0.7828 - 499ms/epoch - 10ms/step
Epoch 950/1500
51/51 - 1s - loss: 0.0647 - categorical_accuracy: 0.9743 - val_loss: 2.1096 - val_categorical_accuracy: 0.7905 - 553ms/epoch - 11ms/step
Epoch 951/1500
51/51 - 1s - loss: 0.0669 - categorical_accuracy: 0.9748 - val_loss: 2.0869 - val_categorical_accuracy: 0.7917 - 508ms/epoch - 10ms/step
Epoch 952/1500
51/51 - 1s - loss: 0.0639 - categorical_accuracy: 0.9754 - val_loss: 2.0861 - val_categorical_accuracy: 0.7882 - 526ms/epoch - 10ms/step
Epoch 953/1500
51/51 - 1s - loss: 0.0636 - categorical_accuracy: 0.9751 - val_loss: 2.1423 - val_categorical_accuracy: 0.7932 - 506ms/epoch - 10ms/step
Epoch 954/1500
51/51 - 1s - loss: 0.0647 - categorical_accuracy: 0.9754 - val_loss: 2.1348 - val_categorical_accuracy: 0.7955 - 543ms/epoch - 11ms/step
Epoch 955/1500
51/51 - 0s - loss: 0.0771 - categorical_accuracy: 0.9708 - val_loss: 2.1264 - val_categorical_accuracy: 0.7766 - 489ms/epoch - 10ms/step
Epoch 956/1500
51/51 - 1s - loss: 0.0730 - categorical_accuracy: 0.9723 - val_loss: 2.1296 - val_categorical_accuracy: 0.7943 - 535ms/epoch - 10ms/step
Epoch 957/1500
51/51 - 0s - loss: 0.0693 - categorical_accuracy: 0.9729 - val_loss: 2.1686 - val_categorical_accuracy: 0.7876 - 489ms/epoch - 10ms/step
Epoch 958/1500
51/51 - 1s - loss: 0.0736 - categorical_accuracy: 0.9723 - val_loss: 2.2647 - val_categorical_accuracy: 0.7952 - 528ms/epoch - 10ms/step
Epoch 959/1500
51/51 - 0s - loss: 0.0663 - categorical_accuracy: 0.9749 - val_loss: 2.1451 - val_categorical_accuracy: 0.7911 - 490ms/epoch - 10ms/step
Epoch 960/1500
51/51 - 1s - loss: 0.0623 - categorical_accuracy: 0.9768 - val_loss: 2.1964 - val_categorical_accuracy: 0.7916 - 549ms/epoch - 11ms/step
Epoch 961/1500
51/51 - 1s - loss: 0.0656 - categorical_accuracy: 0.9741 - val_loss: 2.1257 - val_categorical_accuracy: 0.7874 - 502ms/epoch - 10ms/step
Epoch 962/1500
51/51 - 1s - loss: 0.0654 - categorical_accuracy: 0.9749 - val_loss: 2.1726 - val_categorical_accuracy: 0.7872 - 542ms/epoch - 11ms/step
Epoch 963/1500
51/51 - 1s - loss: 0.0646 - categorical_accuracy: 0.9747 - val_loss: 2.2259 - val_categorical_accuracy: 0.7950 - 516ms/epoch - 10ms/step
Epoch 964/1500
51/51 - 1s - loss: 0.0703 - categorical_accuracy: 0.9741 - val_loss: 2.1975 - val_categorical_accuracy: 0.7822 - 520ms/epoch - 10ms/step
Epoch 965/1500
51/51 - 0s - loss: 0.0760 - categorical_accuracy: 0.9716 - val_loss: 2.1892 - val_categorical_accuracy: 0.7911 - 493ms/epoch - 10ms/step
Epoch 966/1500
51/51 - 1s - loss: 0.0652 - categorical_accuracy: 0.9750 - val_loss: 2.2163 - val_categorical_accuracy: 0.7937 - 523ms/epoch - 10ms/step
Epoch 967/1500
51/51 - 0s - loss: 0.0705 - categorical_accuracy: 0.9738 - val_loss: 2.1909 - val_categorical_accuracy: 0.7875 - 492ms/epoch - 10ms/step
Epoch 968/1500
51/51 - 1s - loss: 0.0777 - categorical_accuracy: 0.9704 - val_loss: 2.1732 - val_categorical_accuracy: 0.7838 - 528ms/epoch - 10ms/step
Epoch 969/1500
51/51 - 0s - loss: 0.0663 - categorical_accuracy: 0.9745 - val_loss: 2.2324 - val_categorical_accuracy: 0.7899 - 459ms/epoch - 9ms/step
Epoch 970/1500
51/51 - 1s - loss: 0.0674 - categorical_accuracy: 0.9741 - val_loss: 2.2460 - val_categorical_accuracy: 0.7885 - 519ms/epoch - 10ms/step
Epoch 971/1500
51/51 - 0s - loss: 0.0681 - categorical_accuracy: 0.9739 - val_loss: 2.2124 - val_categorical_accuracy: 0.7892 - 489ms/epoch - 10ms/step
Epoch 972/1500
51/51 - 1s - loss: 0.0666 - categorical_accuracy: 0.9746 - val_loss: 2.2624 - val_categorical_accuracy: 0.7932 - 509ms/epoch - 10ms/step
Epoch 973/1500
51/51 - 0s - loss: 0.3834 - categorical_accuracy: 0.9087 - val_loss: 1.6310 - val_categorical_accuracy: 0.7828 - 477ms/epoch - 9ms/step
Epoch 974/1500
51/51 - 1s - loss: 0.0978 - categorical_accuracy: 0.9625 - val_loss: 1.8758 - val_categorical_accuracy: 0.7917 - 519ms/epoch - 10ms/step
Epoch 975/1500
51/51 - 0s - loss: 0.0754 - categorical_accuracy: 0.9711 - val_loss: 1.9681 - val_categorical_accuracy: 0.7946 - 476ms/epoch - 9ms/step
Epoch 976/1500
51/51 - 1s - loss: 0.0665 - categorical_accuracy: 0.9753 - val_loss: 2.0051 - val_categorical_accuracy: 0.7917 - 505ms/epoch - 10ms/step
Epoch 977/1500
51/51 - 0s - loss: 0.0661 - categorical_accuracy: 0.9748 - val_loss: 2.1028 - val_categorical_accuracy: 0.7874 - 473ms/epoch - 9ms/step
Epoch 978/1500
51/51 - 1s - loss: 0.0670 - categorical_accuracy: 0.9742 - val_loss: 2.0659 - val_categorical_accuracy: 0.7820 - 505ms/epoch - 10ms/step
Epoch 979/1500
51/51 - 0s - loss: 0.0657 - categorical_accuracy: 0.9750 - val_loss: 2.0759 - val_categorical_accuracy: 0.7921 - 489ms/epoch - 10ms/step
Epoch 980/1500
51/51 - 1s - loss: 0.0641 - categorical_accuracy: 0.9758 - val_loss: 2.1451 - val_categorical_accuracy: 0.7942 - 596ms/epoch - 12ms/step
Epoch 981/1500
51/51 - 1s - loss: 0.0700 - categorical_accuracy: 0.9732 - val_loss: 2.1441 - val_categorical_accuracy: 0.7847 - 536ms/epoch - 11ms/step
Epoch 982/1500
51/51 - 1s - loss: 0.2057 - categorical_accuracy: 0.9381 - val_loss: 1.7584 - val_categorical_accuracy: 0.7785 - 583ms/epoch - 11ms/step
Epoch 983/1500
51/51 - 1s - loss: 0.0977 - categorical_accuracy: 0.9631 - val_loss: 1.9587 - val_categorical_accuracy: 0.7905 - 556ms/epoch - 11ms/step
Epoch 984/1500
51/51 - 1s - loss: 0.0700 - categorical_accuracy: 0.9736 - val_loss: 2.0172 - val_categorical_accuracy: 0.7949 - 536ms/epoch - 11ms/step
Epoch 985/1500
51/51 - 1s - loss: 0.0690 - categorical_accuracy: 0.9733 - val_loss: 2.0397 - val_categorical_accuracy: 0.7874 - 580ms/epoch - 11ms/step
Epoch 986/1500
51/51 - 1s - loss: 0.0616 - categorical_accuracy: 0.9766 - val_loss: 2.1037 - val_categorical_accuracy: 0.7903 - 541ms/epoch - 11ms/step
Epoch 987/1500
51/51 - 1s - loss: 0.0627 - categorical_accuracy: 0.9760 - val_loss: 2.1158 - val_categorical_accuracy: 0.7884 - 525ms/epoch - 10ms/step
Epoch 988/1500
51/51 - 1s - loss: 0.0682 - categorical_accuracy: 0.9736 - val_loss: 2.1499 - val_categorical_accuracy: 0.7874 - 524ms/epoch - 10ms/step
Epoch 989/1500
51/51 - 1s - loss: 0.0624 - categorical_accuracy: 0.9758 - val_loss: 2.1944 - val_categorical_accuracy: 0.7836 - 537ms/epoch - 11ms/step
Epoch 990/1500
51/51 - 1s - loss: 0.0665 - categorical_accuracy: 0.9738 - val_loss: 2.1619 - val_categorical_accuracy: 0.7896 - 516ms/epoch - 10ms/step
Epoch 991/1500
51/51 - 1s - loss: 0.0661 - categorical_accuracy: 0.9736 - val_loss: 2.1649 - val_categorical_accuracy: 0.7877 - 541ms/epoch - 11ms/step
Epoch 992/1500
51/51 - 1s - loss: 0.0665 - categorical_accuracy: 0.9746 - val_loss: 2.2041 - val_categorical_accuracy: 0.7909 - 555ms/epoch - 11ms/step
Epoch 993/1500
51/51 - 1s - loss: 0.0697 - categorical_accuracy: 0.9736 - val_loss: 2.1599 - val_categorical_accuracy: 0.7915 - 526ms/epoch - 10ms/step
Epoch 994/1500
51/51 - 1s - loss: 0.0664 - categorical_accuracy: 0.9743 - val_loss: 2.1628 - val_categorical_accuracy: 0.7928 - 545ms/epoch - 11ms/step
Epoch 995/1500
51/51 - 1s - loss: 0.0609 - categorical_accuracy: 0.9763 - val_loss: 2.1960 - val_categorical_accuracy: 0.7867 - 519ms/epoch - 10ms/step
Epoch 996/1500
51/51 - 1s - loss: 0.0637 - categorical_accuracy: 0.9760 - val_loss: 2.1933 - val_categorical_accuracy: 0.7920 - 555ms/epoch - 11ms/step
Epoch 997/1500
51/51 - 1s - loss: 0.0730 - categorical_accuracy: 0.9718 - val_loss: 2.2381 - val_categorical_accuracy: 0.7879 - 526ms/epoch - 10ms/step
Epoch 998/1500
51/51 - 1s - loss: 0.0691 - categorical_accuracy: 0.9723 - val_loss: 2.2098 - val_categorical_accuracy: 0.7939 - 536ms/epoch - 11ms/step
Epoch 999/1500
51/51 - 1s - loss: 0.0656 - categorical_accuracy: 0.9749 - val_loss: 2.2144 - val_categorical_accuracy: 0.7935 - 514ms/epoch - 10ms/step
Epoch 1000/1500
51/51 - 1s - loss: 0.0624 - categorical_accuracy: 0.9757 - val_loss: 2.2258 - val_categorical_accuracy: 0.7818 - 566ms/epoch - 11ms/step
Epoch 1001/1500
51/51 - 1s - loss: 0.0683 - categorical_accuracy: 0.9731 - val_loss: 2.2032 - val_categorical_accuracy: 0.7884 - 530ms/epoch - 10ms/step
Epoch 1002/1500
51/51 - 1s - loss: 0.0678 - categorical_accuracy: 0.9741 - val_loss: 2.2230 - val_categorical_accuracy: 0.7848 - 576ms/epoch - 11ms/step
Epoch 1003/1500
51/51 - 1s - loss: 0.0640 - categorical_accuracy: 0.9746 - val_loss: 2.2686 - val_categorical_accuracy: 0.7825 - 574ms/epoch - 11ms/step
Epoch 1004/1500
51/51 - 1s - loss: 0.0705 - categorical_accuracy: 0.9727 - val_loss: 2.2646 - val_categorical_accuracy: 0.7784 - 824ms/epoch - 16ms/step
Epoch 1005/1500
51/51 - 1s - loss: 0.0779 - categorical_accuracy: 0.9703 - val_loss: 2.2356 - val_categorical_accuracy: 0.7921 - 573ms/epoch - 11ms/step
Epoch 1006/1500
51/51 - 1s - loss: 0.0708 - categorical_accuracy: 0.9729 - val_loss: 2.2883 - val_categorical_accuracy: 0.7824 - 562ms/epoch - 11ms/step
Epoch 1007/1500
51/51 - 1s - loss: 0.1042 - categorical_accuracy: 0.9610 - val_loss: 2.2176 - val_categorical_accuracy: 0.7716 - 553ms/epoch - 11ms/step
Epoch 1008/1500
51/51 - 1s - loss: 0.0895 - categorical_accuracy: 0.9669 - val_loss: 2.2254 - val_categorical_accuracy: 0.7853 - 561ms/epoch - 11ms/step
Epoch 1009/1500
51/51 - 1s - loss: 0.1079 - categorical_accuracy: 0.9611 - val_loss: 2.1737 - val_categorical_accuracy: 0.7855 - 526ms/epoch - 10ms/step
Epoch 1010/1500
51/51 - 1s - loss: 0.0752 - categorical_accuracy: 0.9712 - val_loss: 2.1434 - val_categorical_accuracy: 0.7874 - 567ms/epoch - 11ms/step
Epoch 1011/1500
51/51 - 1s - loss: 0.0723 - categorical_accuracy: 0.9721 - val_loss: 2.2328 - val_categorical_accuracy: 0.7792 - 512ms/epoch - 10ms/step
Epoch 1012/1500
51/51 - 1s - loss: 0.2469 - categorical_accuracy: 0.9285 - val_loss: 1.9198 - val_categorical_accuracy: 0.7902 - 535ms/epoch - 10ms/step
Epoch 1013/1500
51/51 - 1s - loss: 0.0775 - categorical_accuracy: 0.9708 - val_loss: 2.1496 - val_categorical_accuracy: 0.7973 - 500ms/epoch - 10ms/step
Epoch 1014/1500
51/51 - 1s - loss: 0.0689 - categorical_accuracy: 0.9741 - val_loss: 2.0597 - val_categorical_accuracy: 0.7853 - 543ms/epoch - 11ms/step
Epoch 1015/1500
51/51 - 0s - loss: 0.0663 - categorical_accuracy: 0.9746 - val_loss: 2.1379 - val_categorical_accuracy: 0.7872 - 482ms/epoch - 9ms/step
Epoch 1016/1500
51/51 - 1s - loss: 0.0638 - categorical_accuracy: 0.9748 - val_loss: 2.1245 - val_categorical_accuracy: 0.7841 - 534ms/epoch - 10ms/step
Epoch 1017/1500
51/51 - 1s - loss: 0.0657 - categorical_accuracy: 0.9743 - val_loss: 2.2932 - val_categorical_accuracy: 0.7625 - 559ms/epoch - 11ms/step
Epoch 1018/1500
51/51 - 1s - loss: 0.0740 - categorical_accuracy: 0.9723 - val_loss: 2.2250 - val_categorical_accuracy: 0.7919 - 537ms/epoch - 11ms/step
Epoch 1019/1500
51/51 - 1s - loss: 0.0657 - categorical_accuracy: 0.9738 - val_loss: 2.1711 - val_categorical_accuracy: 0.7897 - 514ms/epoch - 10ms/step
Epoch 1020/1500
51/51 - 1s - loss: 0.0641 - categorical_accuracy: 0.9750 - val_loss: 2.1792 - val_categorical_accuracy: 0.7931 - 539ms/epoch - 11ms/step
Epoch 1021/1500
51/51 - 1s - loss: 0.1867 - categorical_accuracy: 0.9509 - val_loss: 1.7759 - val_categorical_accuracy: 0.7811 - 505ms/epoch - 10ms/step
Epoch 1022/1500
51/51 - 1s - loss: 0.1147 - categorical_accuracy: 0.9569 - val_loss: 2.0519 - val_categorical_accuracy: 0.7837 - 510ms/epoch - 10ms/step
Epoch 1023/1500
51/51 - 1s - loss: 0.0727 - categorical_accuracy: 0.9722 - val_loss: 2.0294 - val_categorical_accuracy: 0.7926 - 516ms/epoch - 10ms/step
Epoch 1024/1500
51/51 - 1s - loss: 0.0643 - categorical_accuracy: 0.9751 - val_loss: 2.1236 - val_categorical_accuracy: 0.7946 - 510ms/epoch - 10ms/step
Epoch 1025/1500
51/51 - 1s - loss: 0.0682 - categorical_accuracy: 0.9740 - val_loss: 2.2142 - val_categorical_accuracy: 0.7918 - 516ms/epoch - 10ms/step
Epoch 1026/1500
51/51 - 1s - loss: 0.0606 - categorical_accuracy: 0.9763 - val_loss: 2.1475 - val_categorical_accuracy: 0.7785 - 537ms/epoch - 11ms/step
Epoch 1027/1500
51/51 - 1s - loss: 0.0599 - categorical_accuracy: 0.9767 - val_loss: 2.2383 - val_categorical_accuracy: 0.7933 - 510ms/epoch - 10ms/step
Epoch 1028/1500
51/51 - 0s - loss: 0.0644 - categorical_accuracy: 0.9748 - val_loss: 2.1710 - val_categorical_accuracy: 0.7841 - 498ms/epoch - 10ms/step
Epoch 1029/1500
51/51 - 1s - loss: 0.0651 - categorical_accuracy: 0.9750 - val_loss: 2.1667 - val_categorical_accuracy: 0.7857 - 523ms/epoch - 10ms/step
Epoch 1030/1500
51/51 - 1s - loss: 0.0661 - categorical_accuracy: 0.9744 - val_loss: 2.2781 - val_categorical_accuracy: 0.7833 - 506ms/epoch - 10ms/step
Epoch 1031/1500
51/51 - 1s - loss: 0.0729 - categorical_accuracy: 0.9721 - val_loss: 2.2649 - val_categorical_accuracy: 0.7915 - 521ms/epoch - 10ms/step
Epoch 1032/1500
51/51 - 1s - loss: 0.0625 - categorical_accuracy: 0.9761 - val_loss: 2.2382 - val_categorical_accuracy: 0.7971 - 515ms/epoch - 10ms/step
Epoch 1033/1500
51/51 - 1s - loss: 0.0610 - categorical_accuracy: 0.9764 - val_loss: 2.2541 - val_categorical_accuracy: 0.7914 - 512ms/epoch - 10ms/step
Epoch 1034/1500
51/51 - 1s - loss: 0.0637 - categorical_accuracy: 0.9750 - val_loss: 2.2454 - val_categorical_accuracy: 0.7900 - 508ms/epoch - 10ms/step
Epoch 1035/1500
51/51 - 1s - loss: 0.0645 - categorical_accuracy: 0.9755 - val_loss: 2.2131 - val_categorical_accuracy: 0.7785 - 530ms/epoch - 10ms/step
Epoch 1036/1500
51/51 - 1s - loss: 0.0631 - categorical_accuracy: 0.9756 - val_loss: 2.2110 - val_categorical_accuracy: 0.7851 - 529ms/epoch - 10ms/step
Epoch 1037/1500
51/51 - 1s - loss: 0.0859 - categorical_accuracy: 0.9670 - val_loss: 2.3631 - val_categorical_accuracy: 0.7891 - 543ms/epoch - 11ms/step
Epoch 1038/1500
51/51 - 1s - loss: 0.3578 - categorical_accuracy: 0.9132 - val_loss: 1.8064 - val_categorical_accuracy: 0.7889 - 513ms/epoch - 10ms/step
Epoch 1039/1500
51/51 - 1s - loss: 0.0783 - categorical_accuracy: 0.9703 - val_loss: 1.9107 - val_categorical_accuracy: 0.7768 - 512ms/epoch - 10ms/step
Epoch 1040/1500
51/51 - 0s - loss: 0.0701 - categorical_accuracy: 0.9732 - val_loss: 1.9893 - val_categorical_accuracy: 0.7880 - 490ms/epoch - 10ms/step
Epoch 1041/1500
51/51 - 1s - loss: 0.0611 - categorical_accuracy: 0.9769 - val_loss: 2.0731 - val_categorical_accuracy: 0.7878 - 535ms/epoch - 10ms/step
Epoch 1042/1500
51/51 - 1s - loss: 0.0600 - categorical_accuracy: 0.9768 - val_loss: 2.0695 - val_categorical_accuracy: 0.7853 - 534ms/epoch - 10ms/step
Epoch 1043/1500
51/51 - 1s - loss: 0.0600 - categorical_accuracy: 0.9766 - val_loss: 2.1615 - val_categorical_accuracy: 0.7949 - 547ms/epoch - 11ms/step
Epoch 1044/1500
51/51 - 1s - loss: 0.0652 - categorical_accuracy: 0.9751 - val_loss: 2.1339 - val_categorical_accuracy: 0.7883 - 565ms/epoch - 11ms/step
Epoch 1045/1500
51/51 - 0s - loss: 0.0633 - categorical_accuracy: 0.9757 - val_loss: 2.1606 - val_categorical_accuracy: 0.7940 - 496ms/epoch - 10ms/step
Epoch 1046/1500
51/51 - 1s - loss: 0.0624 - categorical_accuracy: 0.9745 - val_loss: 2.1398 - val_categorical_accuracy: 0.7897 - 530ms/epoch - 10ms/step
Epoch 1047/1500
51/51 - 1s - loss: 0.0608 - categorical_accuracy: 0.9764 - val_loss: 2.1679 - val_categorical_accuracy: 0.7839 - 509ms/epoch - 10ms/step
Epoch 1048/1500
51/51 - 1s - loss: 0.0602 - categorical_accuracy: 0.9771 - val_loss: 2.2325 - val_categorical_accuracy: 0.7897 - 516ms/epoch - 10ms/step
Epoch 1049/1500
51/51 - 1s - loss: 0.0603 - categorical_accuracy: 0.9773 - val_loss: 2.2264 - val_categorical_accuracy: 0.7921 - 509ms/epoch - 10ms/step
Epoch 1050/1500
51/51 - 1s - loss: 0.0598 - categorical_accuracy: 0.9764 - val_loss: 2.3301 - val_categorical_accuracy: 0.7786 - 541ms/epoch - 11ms/step
Epoch 1051/1500
51/51 - 0s - loss: 0.0717 - categorical_accuracy: 0.9726 - val_loss: 2.2805 - val_categorical_accuracy: 0.7880 - 486ms/epoch - 10ms/step
Epoch 1052/1500
51/51 - 1s - loss: 0.2414 - categorical_accuracy: 0.9326 - val_loss: 2.0748 - val_categorical_accuracy: 0.7657 - 522ms/epoch - 10ms/step
Epoch 1053/1500
51/51 - 1s - loss: 0.0753 - categorical_accuracy: 0.9710 - val_loss: 2.0411 - val_categorical_accuracy: 0.7888 - 509ms/epoch - 10ms/step
Epoch 1054/1500
51/51 - 1s - loss: 0.0686 - categorical_accuracy: 0.9740 - val_loss: 2.1231 - val_categorical_accuracy: 0.7777 - 534ms/epoch - 10ms/step
Epoch 1055/1500
51/51 - 1s - loss: 0.0661 - categorical_accuracy: 0.9745 - val_loss: 2.1506 - val_categorical_accuracy: 0.7912 - 523ms/epoch - 10ms/step
Epoch 1056/1500
51/51 - 1s - loss: 0.0602 - categorical_accuracy: 0.9769 - val_loss: 2.1735 - val_categorical_accuracy: 0.7918 - 565ms/epoch - 11ms/step
Epoch 1057/1500
51/51 - 0s - loss: 0.0607 - categorical_accuracy: 0.9771 - val_loss: 2.2295 - val_categorical_accuracy: 0.7914 - 491ms/epoch - 10ms/step
Epoch 1058/1500
51/51 - 1s - loss: 0.0651 - categorical_accuracy: 0.9751 - val_loss: 2.2414 - val_categorical_accuracy: 0.7806 - 538ms/epoch - 11ms/step
Epoch 1059/1500
51/51 - 1s - loss: 0.0674 - categorical_accuracy: 0.9749 - val_loss: 2.1732 - val_categorical_accuracy: 0.7891 - 511ms/epoch - 10ms/step
Epoch 1060/1500
51/51 - 1s - loss: 0.0592 - categorical_accuracy: 0.9774 - val_loss: 2.1957 - val_categorical_accuracy: 0.7792 - 536ms/epoch - 11ms/step
Epoch 1061/1500
51/51 - 0s - loss: 0.0621 - categorical_accuracy: 0.9761 - val_loss: 2.2834 - val_categorical_accuracy: 0.7766 - 493ms/epoch - 10ms/step
Epoch 1062/1500
51/51 - 1s - loss: 0.0679 - categorical_accuracy: 0.9738 - val_loss: 2.2151 - val_categorical_accuracy: 0.7916 - 522ms/epoch - 10ms/step
Epoch 1063/1500
51/51 - 0s - loss: 0.0621 - categorical_accuracy: 0.9755 - val_loss: 2.2962 - val_categorical_accuracy: 0.7955 - 479ms/epoch - 9ms/step
Epoch 1064/1500
51/51 - 1s - loss: 0.0621 - categorical_accuracy: 0.9761 - val_loss: 2.3148 - val_categorical_accuracy: 0.7748 - 521ms/epoch - 10ms/step
Epoch 1065/1500
51/51 - 0s - loss: 0.2937 - categorical_accuracy: 0.9264 - val_loss: 1.9315 - val_categorical_accuracy: 0.7918 - 490ms/epoch - 10ms/step
Epoch 1066/1500
51/51 - 1s - loss: 0.0717 - categorical_accuracy: 0.9727 - val_loss: 2.0072 - val_categorical_accuracy: 0.7882 - 523ms/epoch - 10ms/step
Epoch 1067/1500
51/51 - 1s - loss: 0.0638 - categorical_accuracy: 0.9749 - val_loss: 2.0439 - val_categorical_accuracy: 0.7892 - 501ms/epoch - 10ms/step
Epoch 1068/1500
51/51 - 1s - loss: 0.0649 - categorical_accuracy: 0.9752 - val_loss: 2.1179 - val_categorical_accuracy: 0.7906 - 555ms/epoch - 11ms/step
Epoch 1069/1500
51/51 - 1s - loss: 0.0613 - categorical_accuracy: 0.9774 - val_loss: 2.1622 - val_categorical_accuracy: 0.7839 - 555ms/epoch - 11ms/step
Epoch 1070/1500
51/51 - 1s - loss: 0.0620 - categorical_accuracy: 0.9758 - val_loss: 2.1333 - val_categorical_accuracy: 0.7810 - 568ms/epoch - 11ms/step
Epoch 1071/1500
51/51 - 1s - loss: 0.0640 - categorical_accuracy: 0.9758 - val_loss: 2.0938 - val_categorical_accuracy: 0.7824 - 583ms/epoch - 11ms/step
Epoch 1072/1500
51/51 - 1s - loss: 0.0655 - categorical_accuracy: 0.9748 - val_loss: 2.2170 - val_categorical_accuracy: 0.7863 - 542ms/epoch - 11ms/step
Epoch 1073/1500
51/51 - 1s - loss: 0.0613 - categorical_accuracy: 0.9764 - val_loss: 2.1788 - val_categorical_accuracy: 0.7904 - 570ms/epoch - 11ms/step
Epoch 1074/1500
51/51 - 1s - loss: 0.0581 - categorical_accuracy: 0.9773 - val_loss: 2.2105 - val_categorical_accuracy: 0.7898 - 564ms/epoch - 11ms/step
Epoch 1075/1500
51/51 - 1s - loss: 0.0622 - categorical_accuracy: 0.9762 - val_loss: 2.3131 - val_categorical_accuracy: 0.7900 - 555ms/epoch - 11ms/step
Epoch 1076/1500
51/51 - 1s - loss: 0.0645 - categorical_accuracy: 0.9746 - val_loss: 2.2334 - val_categorical_accuracy: 0.7894 - 540ms/epoch - 11ms/step
Epoch 1077/1500
51/51 - 1s - loss: 0.0624 - categorical_accuracy: 0.9762 - val_loss: 2.2671 - val_categorical_accuracy: 0.7872 - 557ms/epoch - 11ms/step
Epoch 1078/1500
51/51 - 1s - loss: 0.0628 - categorical_accuracy: 0.9753 - val_loss: 2.2686 - val_categorical_accuracy: 0.7813 - 559ms/epoch - 11ms/step
Epoch 1079/1500
51/51 - 1s - loss: 0.0645 - categorical_accuracy: 0.9750 - val_loss: 2.3094 - val_categorical_accuracy: 0.7949 - 542ms/epoch - 11ms/step
Epoch 1080/1500
51/51 - 1s - loss: 0.0618 - categorical_accuracy: 0.9762 - val_loss: 2.2756 - val_categorical_accuracy: 0.7916 - 545ms/epoch - 11ms/step
Epoch 1081/1500
51/51 - 1s - loss: 0.0611 - categorical_accuracy: 0.9764 - val_loss: 2.3338 - val_categorical_accuracy: 0.7890 - 545ms/epoch - 11ms/step
Epoch 1082/1500
51/51 - 1s - loss: 0.0708 - categorical_accuracy: 0.9728 - val_loss: 2.2842 - val_categorical_accuracy: 0.7889 - 566ms/epoch - 11ms/step
Epoch 1083/1500
51/51 - 1s - loss: 0.0691 - categorical_accuracy: 0.9738 - val_loss: 2.2735 - val_categorical_accuracy: 0.7895 - 520ms/epoch - 10ms/step
Epoch 1084/1500
51/51 - 1s - loss: 0.0593 - categorical_accuracy: 0.9769 - val_loss: 2.3026 - val_categorical_accuracy: 0.7913 - 566ms/epoch - 11ms/step
Epoch 1085/1500
51/51 - 1s - loss: 0.0624 - categorical_accuracy: 0.9762 - val_loss: 2.2915 - val_categorical_accuracy: 0.7928 - 552ms/epoch - 11ms/step
Epoch 1086/1500
51/51 - 1s - loss: 0.0590 - categorical_accuracy: 0.9776 - val_loss: 2.2726 - val_categorical_accuracy: 0.7874 - 540ms/epoch - 11ms/step
Epoch 1087/1500
51/51 - 1s - loss: 0.0582 - categorical_accuracy: 0.9770 - val_loss: 2.3167 - val_categorical_accuracy: 0.7880 - 537ms/epoch - 11ms/step
Epoch 1088/1500
51/51 - 1s - loss: 0.0581 - categorical_accuracy: 0.9774 - val_loss: 2.3055 - val_categorical_accuracy: 0.7880 - 557ms/epoch - 11ms/step
Epoch 1089/1500
51/51 - 1s - loss: 0.0652 - categorical_accuracy: 0.9751 - val_loss: 2.3736 - val_categorical_accuracy: 0.7787 - 573ms/epoch - 11ms/step
Epoch 1090/1500
51/51 - 1s - loss: 0.0734 - categorical_accuracy: 0.9713 - val_loss: 2.2686 - val_categorical_accuracy: 0.7867 - 543ms/epoch - 11ms/step
Epoch 1091/1500
51/51 - 1s - loss: 0.0657 - categorical_accuracy: 0.9749 - val_loss: 2.3198 - val_categorical_accuracy: 0.7838 - 583ms/epoch - 11ms/step
Epoch 1092/1500
51/51 - 1s - loss: 0.0718 - categorical_accuracy: 0.9738 - val_loss: 2.2583 - val_categorical_accuracy: 0.7883 - 559ms/epoch - 11ms/step
Epoch 1093/1500
51/51 - 1s - loss: 0.0736 - categorical_accuracy: 0.9716 - val_loss: 2.3008 - val_categorical_accuracy: 0.7880 - 559ms/epoch - 11ms/step
Epoch 1094/1500
51/51 - 1s - loss: 0.0644 - categorical_accuracy: 0.9758 - val_loss: 2.3321 - val_categorical_accuracy: 0.7883 - 527ms/epoch - 10ms/step
Epoch 1095/1500
51/51 - 1s - loss: 0.0656 - categorical_accuracy: 0.9745 - val_loss: 2.3242 - val_categorical_accuracy: 0.7799 - 541ms/epoch - 11ms/step
Epoch 1096/1500
51/51 - 1s - loss: 0.0702 - categorical_accuracy: 0.9730 - val_loss: 2.2957 - val_categorical_accuracy: 0.7883 - 555ms/epoch - 11ms/step
Epoch 1097/1500
51/51 - 1s - loss: 0.0640 - categorical_accuracy: 0.9749 - val_loss: 2.3017 - val_categorical_accuracy: 0.7869 - 541ms/epoch - 11ms/step
Epoch 1098/1500
51/51 - 1s - loss: 0.0639 - categorical_accuracy: 0.9751 - val_loss: 2.3581 - val_categorical_accuracy: 0.7813 - 559ms/epoch - 11ms/step
Epoch 1099/1500
51/51 - 1s - loss: 0.0647 - categorical_accuracy: 0.9744 - val_loss: 2.3319 - val_categorical_accuracy: 0.7882 - 524ms/epoch - 10ms/step
Epoch 1100/1500
51/51 - 1s - loss: 0.0597 - categorical_accuracy: 0.9770 - val_loss: 2.3684 - val_categorical_accuracy: 0.7779 - 541ms/epoch - 11ms/step
Epoch 1101/1500
51/51 - 0s - loss: 0.0617 - categorical_accuracy: 0.9762 - val_loss: 2.3290 - val_categorical_accuracy: 0.7855 - 494ms/epoch - 10ms/step
Epoch 1102/1500
51/51 - 1s - loss: 0.2869 - categorical_accuracy: 0.9319 - val_loss: 1.8415 - val_categorical_accuracy: 0.7815 - 524ms/epoch - 10ms/step
Epoch 1103/1500
51/51 - 0s - loss: 0.0911 - categorical_accuracy: 0.9658 - val_loss: 2.0928 - val_categorical_accuracy: 0.7910 - 488ms/epoch - 10ms/step
Epoch 1104/1500
51/51 - 1s - loss: 0.0762 - categorical_accuracy: 0.9711 - val_loss: 2.0900 - val_categorical_accuracy: 0.7929 - 537ms/epoch - 11ms/step
Epoch 1105/1500
51/51 - 1s - loss: 0.0614 - categorical_accuracy: 0.9766 - val_loss: 2.1995 - val_categorical_accuracy: 0.7882 - 504ms/epoch - 10ms/step
Epoch 1106/1500
51/51 - 1s - loss: 0.0569 - categorical_accuracy: 0.9787 - val_loss: 2.2030 - val_categorical_accuracy: 0.7888 - 538ms/epoch - 11ms/step
Epoch 1107/1500
51/51 - 0s - loss: 0.0558 - categorical_accuracy: 0.9784 - val_loss: 2.2058 - val_categorical_accuracy: 0.7895 - 492ms/epoch - 10ms/step
Epoch 1108/1500
51/51 - 1s - loss: 0.0568 - categorical_accuracy: 0.9776 - val_loss: 2.2608 - val_categorical_accuracy: 0.7884 - 538ms/epoch - 11ms/step
Epoch 1109/1500
51/51 - 0s - loss: 0.0558 - categorical_accuracy: 0.9792 - val_loss: 2.3076 - val_categorical_accuracy: 0.7877 - 497ms/epoch - 10ms/step
Epoch 1110/1500
51/51 - 1s - loss: 0.0587 - categorical_accuracy: 0.9778 - val_loss: 2.2770 - val_categorical_accuracy: 0.7906 - 566ms/epoch - 11ms/step
Epoch 1111/1500
51/51 - 1s - loss: 0.0662 - categorical_accuracy: 0.9731 - val_loss: 2.3130 - val_categorical_accuracy: 0.7942 - 509ms/epoch - 10ms/step
Epoch 1112/1500
51/51 - 1s - loss: 0.0640 - categorical_accuracy: 0.9759 - val_loss: 2.2660 - val_categorical_accuracy: 0.7863 - 532ms/epoch - 10ms/step
Epoch 1113/1500
51/51 - 1s - loss: 0.0598 - categorical_accuracy: 0.9768 - val_loss: 2.3494 - val_categorical_accuracy: 0.7880 - 528ms/epoch - 10ms/step
Epoch 1114/1500
51/51 - 1s - loss: 0.0601 - categorical_accuracy: 0.9775 - val_loss: 2.3630 - val_categorical_accuracy: 0.7928 - 514ms/epoch - 10ms/step
Epoch 1115/1500
51/51 - 1s - loss: 0.0600 - categorical_accuracy: 0.9766 - val_loss: 2.3797 - val_categorical_accuracy: 0.7843 - 505ms/epoch - 10ms/step
Epoch 1116/1500
51/51 - 1s - loss: 0.0699 - categorical_accuracy: 0.9737 - val_loss: 2.3207 - val_categorical_accuracy: 0.7918 - 502ms/epoch - 10ms/step
Epoch 1117/1500
51/51 - 1s - loss: 0.0892 - categorical_accuracy: 0.9673 - val_loss: 2.1652 - val_categorical_accuracy: 0.7837 - 509ms/epoch - 10ms/step
Epoch 1118/1500
51/51 - 0s - loss: 0.2755 - categorical_accuracy: 0.9253 - val_loss: 1.7867 - val_categorical_accuracy: 0.7812 - 496ms/epoch - 10ms/step
Epoch 1119/1500
51/51 - 1s - loss: 0.0934 - categorical_accuracy: 0.9652 - val_loss: 2.0191 - val_categorical_accuracy: 0.7882 - 510ms/epoch - 10ms/step
Epoch 1120/1500
51/51 - 1s - loss: 0.0682 - categorical_accuracy: 0.9734 - val_loss: 2.1248 - val_categorical_accuracy: 0.7864 - 506ms/epoch - 10ms/step
Epoch 1121/1500
51/51 - 1s - loss: 0.0645 - categorical_accuracy: 0.9748 - val_loss: 2.1800 - val_categorical_accuracy: 0.7906 - 507ms/epoch - 10ms/step
Epoch 1122/1500
51/51 - 1s - loss: 0.0596 - categorical_accuracy: 0.9768 - val_loss: 2.2370 - val_categorical_accuracy: 0.7945 - 517ms/epoch - 10ms/step
Epoch 1123/1500
51/51 - 1s - loss: 0.0594 - categorical_accuracy: 0.9775 - val_loss: 2.1804 - val_categorical_accuracy: 0.7816 - 515ms/epoch - 10ms/step
Epoch 1124/1500
51/51 - 0s - loss: 0.0574 - categorical_accuracy: 0.9779 - val_loss: 2.2507 - val_categorical_accuracy: 0.7912 - 497ms/epoch - 10ms/step
Epoch 1125/1500
51/51 - 1s - loss: 0.0594 - categorical_accuracy: 0.9769 - val_loss: 2.2522 - val_categorical_accuracy: 0.7834 - 509ms/epoch - 10ms/step
Epoch 1126/1500
51/51 - 1s - loss: 0.0619 - categorical_accuracy: 0.9760 - val_loss: 2.2641 - val_categorical_accuracy: 0.7906 - 504ms/epoch - 10ms/step
Epoch 1127/1500
51/51 - 1s - loss: 0.0579 - categorical_accuracy: 0.9779 - val_loss: 2.2670 - val_categorical_accuracy: 0.7806 - 504ms/epoch - 10ms/step
Epoch 1128/1500
51/51 - 1s - loss: 0.0612 - categorical_accuracy: 0.9773 - val_loss: 2.2848 - val_categorical_accuracy: 0.7844 - 504ms/epoch - 10ms/step
Epoch 1129/1500
51/51 - 1s - loss: 0.0596 - categorical_accuracy: 0.9777 - val_loss: 2.2993 - val_categorical_accuracy: 0.7872 - 510ms/epoch - 10ms/step
Epoch 1130/1500
51/51 - 1s - loss: 0.0563 - categorical_accuracy: 0.9775 - val_loss: 2.3478 - val_categorical_accuracy: 0.7877 - 534ms/epoch - 10ms/step
Epoch 1131/1500
51/51 - 1s - loss: 0.0587 - categorical_accuracy: 0.9774 - val_loss: 2.3276 - val_categorical_accuracy: 0.7860 - 524ms/epoch - 10ms/step
Epoch 1132/1500
51/51 - 1s - loss: 0.0609 - categorical_accuracy: 0.9770 - val_loss: 2.3335 - val_categorical_accuracy: 0.7879 - 504ms/epoch - 10ms/step
Epoch 1133/1500
51/51 - 1s - loss: 0.0607 - categorical_accuracy: 0.9773 - val_loss: 2.3405 - val_categorical_accuracy: 0.7873 - 520ms/epoch - 10ms/step
Epoch 1134/1500
51/51 - 0s - loss: 0.0591 - categorical_accuracy: 0.9771 - val_loss: 2.3059 - val_categorical_accuracy: 0.7863 - 494ms/epoch - 10ms/step
Epoch 1135/1500
51/51 - 1s - loss: 0.0621 - categorical_accuracy: 0.9762 - val_loss: 2.3735 - val_categorical_accuracy: 0.7887 - 521ms/epoch - 10ms/step
Epoch 1136/1500
51/51 - 0s - loss: 0.0631 - categorical_accuracy: 0.9757 - val_loss: 2.3580 - val_categorical_accuracy: 0.7826 - 493ms/epoch - 10ms/step
Epoch 1137/1500
51/51 - 1s - loss: 0.0592 - categorical_accuracy: 0.9776 - val_loss: 2.3262 - val_categorical_accuracy: 0.7838 - 526ms/epoch - 10ms/step
Epoch 1138/1500
51/51 - 1s - loss: 0.0598 - categorical_accuracy: 0.9764 - val_loss: 2.3529 - val_categorical_accuracy: 0.7869 - 501ms/epoch - 10ms/step
Epoch 1139/1500
51/51 - 1s - loss: 0.0690 - categorical_accuracy: 0.9727 - val_loss: 2.3307 - val_categorical_accuracy: 0.7852 - 531ms/epoch - 10ms/step
Epoch 1140/1500
51/51 - 0s - loss: 0.0632 - categorical_accuracy: 0.9750 - val_loss: 2.3858 - val_categorical_accuracy: 0.7743 - 493ms/epoch - 10ms/step
Epoch 1141/1500
51/51 - 1s - loss: 0.0774 - categorical_accuracy: 0.9700 - val_loss: 2.3191 - val_categorical_accuracy: 0.7836 - 524ms/epoch - 10ms/step
Epoch 1142/1500
51/51 - 0s - loss: 0.2498 - categorical_accuracy: 0.9372 - val_loss: 1.8527 - val_categorical_accuracy: 0.7870 - 494ms/epoch - 10ms/step
Epoch 1143/1500
51/51 - 1s - loss: 0.1348 - categorical_accuracy: 0.9508 - val_loss: 1.9543 - val_categorical_accuracy: 0.7855 - 536ms/epoch - 11ms/step
Epoch 1144/1500
51/51 - 0s - loss: 0.0733 - categorical_accuracy: 0.9717 - val_loss: 2.1296 - val_categorical_accuracy: 0.7887 - 494ms/epoch - 10ms/step
Epoch 1145/1500
51/51 - 1s - loss: 0.0603 - categorical_accuracy: 0.9769 - val_loss: 2.1445 - val_categorical_accuracy: 0.7907 - 525ms/epoch - 10ms/step
Epoch 1146/1500
51/51 - 1s - loss: 0.0581 - categorical_accuracy: 0.9783 - val_loss: 2.2189 - val_categorical_accuracy: 0.7929 - 502ms/epoch - 10ms/step
Epoch 1147/1500
51/51 - 1s - loss: 0.0625 - categorical_accuracy: 0.9760 - val_loss: 2.2379 - val_categorical_accuracy: 0.7924 - 528ms/epoch - 10ms/step
Epoch 1148/1500
51/51 - 0s - loss: 0.0608 - categorical_accuracy: 0.9763 - val_loss: 2.2530 - val_categorical_accuracy: 0.7828 - 500ms/epoch - 10ms/step
Epoch 1149/1500
51/51 - 1s - loss: 0.0594 - categorical_accuracy: 0.9768 - val_loss: 2.2521 - val_categorical_accuracy: 0.7858 - 538ms/epoch - 11ms/step
Epoch 1150/1500
51/51 - 1s - loss: 0.0574 - categorical_accuracy: 0.9785 - val_loss: 2.2816 - val_categorical_accuracy: 0.7817 - 506ms/epoch - 10ms/step
Epoch 1151/1500
51/51 - 1s - loss: 0.0598 - categorical_accuracy: 0.9771 - val_loss: 2.3388 - val_categorical_accuracy: 0.7874 - 512ms/epoch - 10ms/step
Epoch 1152/1500
51/51 - 1s - loss: 0.0590 - categorical_accuracy: 0.9770 - val_loss: 2.3314 - val_categorical_accuracy: 0.7872 - 502ms/epoch - 10ms/step
Epoch 1153/1500
51/51 - 1s - loss: 0.0657 - categorical_accuracy: 0.9740 - val_loss: 2.3194 - val_categorical_accuracy: 0.7881 - 501ms/epoch - 10ms/step
Epoch 1154/1500
51/51 - 1s - loss: 0.0627 - categorical_accuracy: 0.9764 - val_loss: 2.3250 - val_categorical_accuracy: 0.7805 - 521ms/epoch - 10ms/step
Epoch 1155/1500
51/51 - 1s - loss: 0.0610 - categorical_accuracy: 0.9770 - val_loss: 2.3627 - val_categorical_accuracy: 0.7898 - 526ms/epoch - 10ms/step
Epoch 1156/1500
51/51 - 1s - loss: 0.0607 - categorical_accuracy: 0.9762 - val_loss: 2.3807 - val_categorical_accuracy: 0.7950 - 526ms/epoch - 10ms/step
Epoch 1157/1500
51/51 - 1s - loss: 0.0617 - categorical_accuracy: 0.9770 - val_loss: 2.3511 - val_categorical_accuracy: 0.7923 - 555ms/epoch - 11ms/step
Epoch 1158/1500
51/51 - 1s - loss: 0.0617 - categorical_accuracy: 0.9762 - val_loss: 2.3827 - val_categorical_accuracy: 0.7917 - 564ms/epoch - 11ms/step
Epoch 1159/1500
51/51 - 1s - loss: 0.0622 - categorical_accuracy: 0.9757 - val_loss: 2.3540 - val_categorical_accuracy: 0.7746 - 537ms/epoch - 11ms/step
Epoch 1160/1500
51/51 - 1s - loss: 0.0624 - categorical_accuracy: 0.9765 - val_loss: 2.3983 - val_categorical_accuracy: 0.7940 - 571ms/epoch - 11ms/step
Epoch 1161/1500
51/51 - 1s - loss: 0.0582 - categorical_accuracy: 0.9772 - val_loss: 2.3426 - val_categorical_accuracy: 0.7804 - 523ms/epoch - 10ms/step
Epoch 1162/1500
51/51 - 1s - loss: 0.0627 - categorical_accuracy: 0.9756 - val_loss: 2.3870 - val_categorical_accuracy: 0.7890 - 568ms/epoch - 11ms/step
Epoch 1163/1500
51/51 - 1s - loss: 0.0560 - categorical_accuracy: 0.9777 - val_loss: 2.3960 - val_categorical_accuracy: 0.7843 - 517ms/epoch - 10ms/step
Epoch 1164/1500
51/51 - 1s - loss: 0.0709 - categorical_accuracy: 0.9730 - val_loss: 2.3024 - val_categorical_accuracy: 0.7879 - 547ms/epoch - 11ms/step
Epoch 1165/1500
51/51 - 1s - loss: 0.0659 - categorical_accuracy: 0.9743 - val_loss: 2.5077 - val_categorical_accuracy: 0.7904 - 556ms/epoch - 11ms/step
Epoch 1166/1500
51/51 - 1s - loss: 0.3423 - categorical_accuracy: 0.9151 - val_loss: 2.0034 - val_categorical_accuracy: 0.7685 - 540ms/epoch - 11ms/step
Epoch 1167/1500
51/51 - 1s - loss: 0.1004 - categorical_accuracy: 0.9619 - val_loss: 2.0931 - val_categorical_accuracy: 0.7846 - 555ms/epoch - 11ms/step
Epoch 1168/1500
51/51 - 1s - loss: 0.0688 - categorical_accuracy: 0.9736 - val_loss: 2.1166 - val_categorical_accuracy: 0.7857 - 559ms/epoch - 11ms/step
Epoch 1169/1500
51/51 - 1s - loss: 0.0567 - categorical_accuracy: 0.9783 - val_loss: 2.2060 - val_categorical_accuracy: 0.7941 - 560ms/epoch - 11ms/step
Epoch 1170/1500
51/51 - 1s - loss: 0.0569 - categorical_accuracy: 0.9774 - val_loss: 2.2203 - val_categorical_accuracy: 0.7915 - 527ms/epoch - 10ms/step
Epoch 1171/1500
51/51 - 1s - loss: 0.0600 - categorical_accuracy: 0.9770 - val_loss: 2.2394 - val_categorical_accuracy: 0.7872 - 570ms/epoch - 11ms/step
Epoch 1172/1500
51/51 - 1s - loss: 0.0563 - categorical_accuracy: 0.9788 - val_loss: 2.3325 - val_categorical_accuracy: 0.7927 - 522ms/epoch - 10ms/step
Epoch 1173/1500
51/51 - 1s - loss: 0.0579 - categorical_accuracy: 0.9772 - val_loss: 2.2447 - val_categorical_accuracy: 0.7856 - 557ms/epoch - 11ms/step
Epoch 1174/1500
51/51 - 1s - loss: 0.0596 - categorical_accuracy: 0.9779 - val_loss: 2.2948 - val_categorical_accuracy: 0.7900 - 540ms/epoch - 11ms/step
Epoch 1175/1500
51/51 - 1s - loss: 0.0560 - categorical_accuracy: 0.9788 - val_loss: 2.2848 - val_categorical_accuracy: 0.7832 - 538ms/epoch - 11ms/step
Epoch 1176/1500
51/51 - 1s - loss: 0.0566 - categorical_accuracy: 0.9774 - val_loss: 2.3487 - val_categorical_accuracy: 0.7936 - 542ms/epoch - 11ms/step
Epoch 1177/1500
51/51 - 1s - loss: 0.0576 - categorical_accuracy: 0.9780 - val_loss: 2.3688 - val_categorical_accuracy: 0.7914 - 538ms/epoch - 11ms/step
Epoch 1178/1500
51/51 - 1s - loss: 0.0642 - categorical_accuracy: 0.9746 - val_loss: 2.4054 - val_categorical_accuracy: 0.7836 - 558ms/epoch - 11ms/step
Epoch 1179/1500
51/51 - 1s - loss: 0.0607 - categorical_accuracy: 0.9767 - val_loss: 2.3426 - val_categorical_accuracy: 0.7886 - 536ms/epoch - 11ms/step
Epoch 1180/1500
51/51 - 1s - loss: 0.0551 - categorical_accuracy: 0.9787 - val_loss: 2.3828 - val_categorical_accuracy: 0.7815 - 555ms/epoch - 11ms/step
Epoch 1181/1500
51/51 - 1s - loss: 0.0550 - categorical_accuracy: 0.9792 - val_loss: 2.4028 - val_categorical_accuracy: 0.7829 - 526ms/epoch - 10ms/step
Epoch 1182/1500
51/51 - 1s - loss: 0.0669 - categorical_accuracy: 0.9746 - val_loss: 2.3917 - val_categorical_accuracy: 0.7956 - 560ms/epoch - 11ms/step
Epoch 1183/1500
51/51 - 1s - loss: 0.0647 - categorical_accuracy: 0.9748 - val_loss: 2.3486 - val_categorical_accuracy: 0.7816 - 516ms/epoch - 10ms/step
Epoch 1184/1500
51/51 - 1s - loss: 0.0634 - categorical_accuracy: 0.9760 - val_loss: 2.3677 - val_categorical_accuracy: 0.7926 - 577ms/epoch - 11ms/step
Epoch 1185/1500
51/51 - 1s - loss: 0.0638 - categorical_accuracy: 0.9753 - val_loss: 2.4507 - val_categorical_accuracy: 0.7889 - 537ms/epoch - 11ms/step
Epoch 1186/1500
51/51 - 1s - loss: 0.1365 - categorical_accuracy: 0.9530 - val_loss: 2.3207 - val_categorical_accuracy: 0.7882 - 549ms/epoch - 11ms/step
Epoch 1187/1500
51/51 - 1s - loss: 0.0676 - categorical_accuracy: 0.9741 - val_loss: 2.2459 - val_categorical_accuracy: 0.7878 - 568ms/epoch - 11ms/step
Epoch 1188/1500
51/51 - 1s - loss: 0.0598 - categorical_accuracy: 0.9762 - val_loss: 2.3265 - val_categorical_accuracy: 0.7840 - 550ms/epoch - 11ms/step
Epoch 1189/1500
51/51 - 1s - loss: 0.0536 - categorical_accuracy: 0.9794 - val_loss: 2.3826 - val_categorical_accuracy: 0.7855 - 557ms/epoch - 11ms/step
Epoch 1190/1500
51/51 - 1s - loss: 0.0594 - categorical_accuracy: 0.9772 - val_loss: 2.3678 - val_categorical_accuracy: 0.7850 - 543ms/epoch - 11ms/step
Epoch 1191/1500
51/51 - 1s - loss: 0.0575 - categorical_accuracy: 0.9781 - val_loss: 2.3636 - val_categorical_accuracy: 0.7870 - 563ms/epoch - 11ms/step
Epoch 1192/1500
51/51 - 1s - loss: 0.0579 - categorical_accuracy: 0.9776 - val_loss: 2.3831 - val_categorical_accuracy: 0.7832 - 530ms/epoch - 10ms/step
Epoch 1193/1500
51/51 - 1s - loss: 0.0640 - categorical_accuracy: 0.9763 - val_loss: 2.4248 - val_categorical_accuracy: 0.7937 - 569ms/epoch - 11ms/step
Epoch 1194/1500
51/51 - 1s - loss: 0.0640 - categorical_accuracy: 0.9753 - val_loss: 2.3778 - val_categorical_accuracy: 0.7851 - 547ms/epoch - 11ms/step
Epoch 1195/1500
51/51 - 1s - loss: 0.0579 - categorical_accuracy: 0.9772 - val_loss: 2.4413 - val_categorical_accuracy: 0.7849 - 562ms/epoch - 11ms/step
Epoch 1196/1500
51/51 - 1s - loss: 0.0620 - categorical_accuracy: 0.9760 - val_loss: 2.3860 - val_categorical_accuracy: 0.7920 - 539ms/epoch - 11ms/step
Epoch 1197/1500
51/51 - 1s - loss: 0.0763 - categorical_accuracy: 0.9708 - val_loss: 2.4468 - val_categorical_accuracy: 0.7844 - 531ms/epoch - 10ms/step
Epoch 1198/1500
51/51 - 1s - loss: 0.0589 - categorical_accuracy: 0.9774 - val_loss: 2.3866 - val_categorical_accuracy: 0.7862 - 558ms/epoch - 11ms/step
Epoch 1199/1500
51/51 - 1s - loss: 0.0539 - categorical_accuracy: 0.9789 - val_loss: 2.4228 - val_categorical_accuracy: 0.7842 - 520ms/epoch - 10ms/step
Epoch 1200/1500
51/51 - 1s - loss: 0.0623 - categorical_accuracy: 0.9758 - val_loss: 2.4658 - val_categorical_accuracy: 0.7908 - 539ms/epoch - 11ms/step
Epoch 1201/1500
51/51 - 1s - loss: 0.0601 - categorical_accuracy: 0.9761 - val_loss: 2.4878 - val_categorical_accuracy: 0.7848 - 500ms/epoch - 10ms/step
Epoch 1202/1500
51/51 - 1s - loss: 0.3894 - categorical_accuracy: 0.9181 - val_loss: 1.4094 - val_categorical_accuracy: 0.7672 - 523ms/epoch - 10ms/step
Epoch 1203/1500
51/51 - 0s - loss: 0.1433 - categorical_accuracy: 0.9462 - val_loss: 2.0619 - val_categorical_accuracy: 0.7626 - 475ms/epoch - 9ms/step
Epoch 1204/1500
51/51 - 1s - loss: 0.0863 - categorical_accuracy: 0.9665 - val_loss: 2.0912 - val_categorical_accuracy: 0.7888 - 510ms/epoch - 10ms/step
Epoch 1205/1500
51/51 - 1s - loss: 0.0661 - categorical_accuracy: 0.9742 - val_loss: 2.1284 - val_categorical_accuracy: 0.7870 - 525ms/epoch - 10ms/step
Epoch 1206/1500
51/51 - 1s - loss: 0.0592 - categorical_accuracy: 0.9766 - val_loss: 2.2227 - val_categorical_accuracy: 0.7872 - 533ms/epoch - 10ms/step
Epoch 1207/1500
51/51 - 0s - loss: 0.0619 - categorical_accuracy: 0.9765 - val_loss: 2.2522 - val_categorical_accuracy: 0.7914 - 489ms/epoch - 10ms/step
Epoch 1208/1500
51/51 - 1s - loss: 0.0527 - categorical_accuracy: 0.9800 - val_loss: 2.2913 - val_categorical_accuracy: 0.7914 - 526ms/epoch - 10ms/step
Epoch 1209/1500
51/51 - 0s - loss: 0.0532 - categorical_accuracy: 0.9797 - val_loss: 2.2831 - val_categorical_accuracy: 0.7884 - 487ms/epoch - 10ms/step
Epoch 1210/1500
51/51 - 1s - loss: 0.0536 - categorical_accuracy: 0.9794 - val_loss: 2.3360 - val_categorical_accuracy: 0.7918 - 539ms/epoch - 11ms/step
Epoch 1211/1500
51/51 - 0s - loss: 0.0629 - categorical_accuracy: 0.9752 - val_loss: 2.3480 - val_categorical_accuracy: 0.7897 - 492ms/epoch - 10ms/step
Epoch 1212/1500
51/51 - 1s - loss: 0.0576 - categorical_accuracy: 0.9774 - val_loss: 2.3612 - val_categorical_accuracy: 0.7929 - 518ms/epoch - 10ms/step
Epoch 1213/1500
51/51 - 1s - loss: 0.0537 - categorical_accuracy: 0.9796 - val_loss: 2.3852 - val_categorical_accuracy: 0.7891 - 500ms/epoch - 10ms/step
Epoch 1214/1500
51/51 - 1s - loss: 0.0611 - categorical_accuracy: 0.9768 - val_loss: 2.3783 - val_categorical_accuracy: 0.7890 - 524ms/epoch - 10ms/step
Epoch 1215/1500
51/51 - 0s - loss: 0.0682 - categorical_accuracy: 0.9733 - val_loss: 2.3477 - val_categorical_accuracy: 0.7896 - 471ms/epoch - 9ms/step
Epoch 1216/1500
51/51 - 1s - loss: 0.0596 - categorical_accuracy: 0.9765 - val_loss: 2.3430 - val_categorical_accuracy: 0.7840 - 516ms/epoch - 10ms/step
Epoch 1217/1500
51/51 - 1s - loss: 0.0559 - categorical_accuracy: 0.9782 - val_loss: 2.3281 - val_categorical_accuracy: 0.7869 - 501ms/epoch - 10ms/step
Epoch 1218/1500
51/51 - 1s - loss: 0.0560 - categorical_accuracy: 0.9784 - val_loss: 2.4437 - val_categorical_accuracy: 0.7945 - 514ms/epoch - 10ms/step
Epoch 1219/1500
51/51 - 0s - loss: 0.0531 - categorical_accuracy: 0.9797 - val_loss: 2.3627 - val_categorical_accuracy: 0.7888 - 491ms/epoch - 10ms/step
Epoch 1220/1500
51/51 - 1s - loss: 0.0586 - categorical_accuracy: 0.9770 - val_loss: 2.4232 - val_categorical_accuracy: 0.7768 - 516ms/epoch - 10ms/step
Epoch 1221/1500
51/51 - 0s - loss: 0.0599 - categorical_accuracy: 0.9776 - val_loss: 2.3810 - val_categorical_accuracy: 0.7814 - 498ms/epoch - 10ms/step
Epoch 1222/1500
51/51 - 1s - loss: 0.0557 - categorical_accuracy: 0.9790 - val_loss: 2.4403 - val_categorical_accuracy: 0.7871 - 525ms/epoch - 10ms/step
Epoch 1223/1500
51/51 - 1s - loss: 0.0565 - categorical_accuracy: 0.9777 - val_loss: 2.5007 - val_categorical_accuracy: 0.7874 - 501ms/epoch - 10ms/step
Epoch 1224/1500
51/51 - 1s - loss: 0.0585 - categorical_accuracy: 0.9774 - val_loss: 2.3882 - val_categorical_accuracy: 0.7883 - 538ms/epoch - 11ms/step
Epoch 1225/1500
51/51 - 0s - loss: 0.0601 - categorical_accuracy: 0.9766 - val_loss: 2.4416 - val_categorical_accuracy: 0.7897 - 494ms/epoch - 10ms/step
Epoch 1226/1500
51/51 - 1s - loss: 0.0625 - categorical_accuracy: 0.9763 - val_loss: 2.5558 - val_categorical_accuracy: 0.7772 - 516ms/epoch - 10ms/step
Epoch 1227/1500
51/51 - 1s - loss: 0.0673 - categorical_accuracy: 0.9741 - val_loss: 2.4224 - val_categorical_accuracy: 0.7818 - 506ms/epoch - 10ms/step
Epoch 1228/1500
51/51 - 1s - loss: 0.0601 - categorical_accuracy: 0.9764 - val_loss: 2.4674 - val_categorical_accuracy: 0.7949 - 506ms/epoch - 10ms/step
Epoch 1229/1500
51/51 - 1s - loss: 0.0563 - categorical_accuracy: 0.9782 - val_loss: 2.5227 - val_categorical_accuracy: 0.7875 - 504ms/epoch - 10ms/step
Epoch 1230/1500
51/51 - 1s - loss: 0.0554 - categorical_accuracy: 0.9780 - val_loss: 2.4906 - val_categorical_accuracy: 0.7909 - 504ms/epoch - 10ms/step
Epoch 1231/1500
51/51 - 1s - loss: 0.0551 - categorical_accuracy: 0.9789 - val_loss: 2.4417 - val_categorical_accuracy: 0.7906 - 506ms/epoch - 10ms/step
Epoch 1232/1500
51/51 - 1s - loss: 0.0566 - categorical_accuracy: 0.9777 - val_loss: 2.4481 - val_categorical_accuracy: 0.7880 - 503ms/epoch - 10ms/step
Epoch 1233/1500
51/51 - 1s - loss: 0.0570 - categorical_accuracy: 0.9780 - val_loss: 2.5006 - val_categorical_accuracy: 0.7889 - 512ms/epoch - 10ms/step
Epoch 1234/1500
51/51 - 0s - loss: 0.0545 - categorical_accuracy: 0.9782 - val_loss: 2.4973 - val_categorical_accuracy: 0.7921 - 497ms/epoch - 10ms/step
Epoch 1235/1500
51/51 - 0s - loss: 0.0567 - categorical_accuracy: 0.9779 - val_loss: 2.4968 - val_categorical_accuracy: 0.7888 - 492ms/epoch - 10ms/step
Epoch 1236/1500
51/51 - 0s - loss: 0.0621 - categorical_accuracy: 0.9769 - val_loss: 2.4464 - val_categorical_accuracy: 0.7884 - 493ms/epoch - 10ms/step
Epoch 1237/1500
51/51 - 1s - loss: 0.0571 - categorical_accuracy: 0.9772 - val_loss: 2.5570 - val_categorical_accuracy: 0.7850 - 507ms/epoch - 10ms/step
Epoch 1238/1500
51/51 - 0s - loss: 0.0745 - categorical_accuracy: 0.9713 - val_loss: 2.4746 - val_categorical_accuracy: 0.7929 - 493ms/epoch - 10ms/step
Epoch 1239/1500
51/51 - 1s - loss: 0.0609 - categorical_accuracy: 0.9769 - val_loss: 2.4634 - val_categorical_accuracy: 0.7847 - 509ms/epoch - 10ms/step
Epoch 1240/1500
51/51 - 1s - loss: 0.0602 - categorical_accuracy: 0.9761 - val_loss: 2.5239 - val_categorical_accuracy: 0.7915 - 510ms/epoch - 10ms/step
Epoch 1241/1500
51/51 - 1s - loss: 0.0614 - categorical_accuracy: 0.9772 - val_loss: 2.5045 - val_categorical_accuracy: 0.7811 - 506ms/epoch - 10ms/step
Epoch 1242/1500
51/51 - 0s - loss: 0.0635 - categorical_accuracy: 0.9763 - val_loss: 2.5582 - val_categorical_accuracy: 0.7839 - 494ms/epoch - 10ms/step
Epoch 1243/1500
51/51 - 1s - loss: 0.0582 - categorical_accuracy: 0.9776 - val_loss: 2.5722 - val_categorical_accuracy: 0.7847 - 524ms/epoch - 10ms/step
Epoch 1244/1500
51/51 - 1s - loss: 0.0535 - categorical_accuracy: 0.9791 - val_loss: 2.5333 - val_categorical_accuracy: 0.7809 - 518ms/epoch - 10ms/step
Epoch 1245/1500
51/51 - 1s - loss: 0.3465 - categorical_accuracy: 0.9329 - val_loss: 1.4309 - val_categorical_accuracy: 0.7621 - 522ms/epoch - 10ms/step
Epoch 1246/1500
51/51 - 0s - loss: 0.2147 - categorical_accuracy: 0.9248 - val_loss: 1.9311 - val_categorical_accuracy: 0.7832 - 477ms/epoch - 9ms/step
Epoch 1247/1500
51/51 - 1s - loss: 0.0795 - categorical_accuracy: 0.9707 - val_loss: 2.0473 - val_categorical_accuracy: 0.7868 - 508ms/epoch - 10ms/step
Epoch 1248/1500
51/51 - 0s - loss: 0.0623 - categorical_accuracy: 0.9761 - val_loss: 2.2132 - val_categorical_accuracy: 0.7946 - 496ms/epoch - 10ms/step
Epoch 1249/1500
51/51 - 1s - loss: 0.0592 - categorical_accuracy: 0.9772 - val_loss: 2.2173 - val_categorical_accuracy: 0.7877 - 519ms/epoch - 10ms/step
Epoch 1250/1500
51/51 - 1s - loss: 0.0589 - categorical_accuracy: 0.9776 - val_loss: 2.2788 - val_categorical_accuracy: 0.7924 - 501ms/epoch - 10ms/step
Epoch 1251/1500
51/51 - 1s - loss: 0.0552 - categorical_accuracy: 0.9793 - val_loss: 2.2837 - val_categorical_accuracy: 0.7911 - 504ms/epoch - 10ms/step
Epoch 1252/1500
51/51 - 1s - loss: 0.0556 - categorical_accuracy: 0.9790 - val_loss: 2.3160 - val_categorical_accuracy: 0.7830 - 510ms/epoch - 10ms/step
Epoch 1253/1500
51/51 - 1s - loss: 0.0527 - categorical_accuracy: 0.9797 - val_loss: 2.3148 - val_categorical_accuracy: 0.7859 - 568ms/epoch - 11ms/step
Epoch 1254/1500
51/51 - 1s - loss: 0.0529 - categorical_accuracy: 0.9797 - val_loss: 2.3384 - val_categorical_accuracy: 0.7803 - 519ms/epoch - 10ms/step
Epoch 1255/1500
51/51 - 1s - loss: 0.0553 - categorical_accuracy: 0.9784 - val_loss: 2.3845 - val_categorical_accuracy: 0.7874 - 558ms/epoch - 11ms/step
Epoch 1256/1500
51/51 - 1s - loss: 0.0531 - categorical_accuracy: 0.9792 - val_loss: 2.3599 - val_categorical_accuracy: 0.7898 - 537ms/epoch - 11ms/step
Epoch 1257/1500
51/51 - 1s - loss: 0.0560 - categorical_accuracy: 0.9784 - val_loss: 2.3759 - val_categorical_accuracy: 0.7852 - 563ms/epoch - 11ms/step
Epoch 1258/1500
51/51 - 1s - loss: 0.0592 - categorical_accuracy: 0.9773 - val_loss: 2.4183 - val_categorical_accuracy: 0.7927 - 531ms/epoch - 10ms/step
Epoch 1259/1500
51/51 - 1s - loss: 0.0514 - categorical_accuracy: 0.9804 - val_loss: 2.4052 - val_categorical_accuracy: 0.7841 - 540ms/epoch - 11ms/step
Epoch 1260/1500
51/51 - 1s - loss: 0.0571 - categorical_accuracy: 0.9779 - val_loss: 2.4345 - val_categorical_accuracy: 0.7839 - 545ms/epoch - 11ms/step
Epoch 1261/1500
51/51 - 1s - loss: 0.0653 - categorical_accuracy: 0.9760 - val_loss: 2.3971 - val_categorical_accuracy: 0.7882 - 541ms/epoch - 11ms/step
Epoch 1262/1500
51/51 - 1s - loss: 0.0596 - categorical_accuracy: 0.9770 - val_loss: 2.4608 - val_categorical_accuracy: 0.7934 - 546ms/epoch - 11ms/step
Epoch 1263/1500
51/51 - 1s - loss: 0.0619 - categorical_accuracy: 0.9757 - val_loss: 2.4205 - val_categorical_accuracy: 0.7850 - 561ms/epoch - 11ms/step
Epoch 1264/1500
51/51 - 1s - loss: 0.0629 - categorical_accuracy: 0.9751 - val_loss: 2.4086 - val_categorical_accuracy: 0.7849 - 589ms/epoch - 12ms/step
Epoch 1265/1500
51/51 - 1s - loss: 0.0585 - categorical_accuracy: 0.9769 - val_loss: 2.4154 - val_categorical_accuracy: 0.7903 - 539ms/epoch - 11ms/step
Epoch 1266/1500
51/51 - 1s - loss: 0.0599 - categorical_accuracy: 0.9770 - val_loss: 2.4216 - val_categorical_accuracy: 0.7802 - 568ms/epoch - 11ms/step
Epoch 1267/1500
51/51 - 1s - loss: 0.0566 - categorical_accuracy: 0.9789 - val_loss: 2.4755 - val_categorical_accuracy: 0.7922 - 541ms/epoch - 11ms/step
Epoch 1268/1500
51/51 - 1s - loss: 0.0759 - categorical_accuracy: 0.9713 - val_loss: 2.3603 - val_categorical_accuracy: 0.7867 - 537ms/epoch - 11ms/step
Epoch 1269/1500
51/51 - 1s - loss: 0.0605 - categorical_accuracy: 0.9769 - val_loss: 2.4275 - val_categorical_accuracy: 0.7742 - 524ms/epoch - 10ms/step
Epoch 1270/1500
51/51 - 1s - loss: 0.0583 - categorical_accuracy: 0.9775 - val_loss: 2.4676 - val_categorical_accuracy: 0.7821 - 557ms/epoch - 11ms/step
Epoch 1271/1500
51/51 - 1s - loss: 0.0624 - categorical_accuracy: 0.9761 - val_loss: 2.4307 - val_categorical_accuracy: 0.7850 - 546ms/epoch - 11ms/step
Epoch 1272/1500
51/51 - 1s - loss: 0.0599 - categorical_accuracy: 0.9769 - val_loss: 2.4763 - val_categorical_accuracy: 0.7861 - 546ms/epoch - 11ms/step
Epoch 1273/1500
51/51 - 1s - loss: 0.0560 - categorical_accuracy: 0.9782 - val_loss: 2.4868 - val_categorical_accuracy: 0.7874 - 558ms/epoch - 11ms/step
Epoch 1274/1500
51/51 - 1s - loss: 0.0565 - categorical_accuracy: 0.9789 - val_loss: 2.4933 - val_categorical_accuracy: 0.7901 - 557ms/epoch - 11ms/step
Epoch 1275/1500
51/51 - 1s - loss: 0.0550 - categorical_accuracy: 0.9786 - val_loss: 2.4838 - val_categorical_accuracy: 0.7897 - 569ms/epoch - 11ms/step
Epoch 1276/1500
51/51 - 1s - loss: 0.0547 - categorical_accuracy: 0.9786 - val_loss: 2.5051 - val_categorical_accuracy: 0.7873 - 534ms/epoch - 10ms/step
Epoch 1277/1500
51/51 - 1s - loss: 0.0576 - categorical_accuracy: 0.9784 - val_loss: 2.5407 - val_categorical_accuracy: 0.7855 - 554ms/epoch - 11ms/step
Epoch 1278/1500
51/51 - 1s - loss: 0.0543 - categorical_accuracy: 0.9792 - val_loss: 2.5167 - val_categorical_accuracy: 0.7855 - 556ms/epoch - 11ms/step
Epoch 1279/1500
51/51 - 1s - loss: 0.0568 - categorical_accuracy: 0.9779 - val_loss: 2.5251 - val_categorical_accuracy: 0.7756 - 552ms/epoch - 11ms/step
Epoch 1280/1500
51/51 - 1s - loss: 0.0592 - categorical_accuracy: 0.9774 - val_loss: 2.5277 - val_categorical_accuracy: 0.7906 - 521ms/epoch - 10ms/step
Epoch 1281/1500
51/51 - 1s - loss: 0.0511 - categorical_accuracy: 0.9807 - val_loss: 2.5845 - val_categorical_accuracy: 0.7955 - 574ms/epoch - 11ms/step
Epoch 1282/1500
51/51 - 1s - loss: 0.0522 - categorical_accuracy: 0.9789 - val_loss: 2.5461 - val_categorical_accuracy: 0.7877 - 576ms/epoch - 11ms/step
Epoch 1283/1500
51/51 - 1s - loss: 0.0534 - categorical_accuracy: 0.9801 - val_loss: 2.6210 - val_categorical_accuracy: 0.7859 - 530ms/epoch - 10ms/step
Epoch 1284/1500
51/51 - 1s - loss: 0.0544 - categorical_accuracy: 0.9787 - val_loss: 2.5273 - val_categorical_accuracy: 0.7847 - 558ms/epoch - 11ms/step
Epoch 1285/1500
51/51 - 1s - loss: 0.0533 - categorical_accuracy: 0.9798 - val_loss: 2.6234 - val_categorical_accuracy: 0.7835 - 532ms/epoch - 10ms/step
Epoch 1286/1500
51/51 - 1s - loss: 0.1243 - categorical_accuracy: 0.9594 - val_loss: 3.0447 - val_categorical_accuracy: 0.6615 - 535ms/epoch - 10ms/step
Epoch 1287/1500
51/51 - 1s - loss: 0.4250 - categorical_accuracy: 0.8943 - val_loss: 1.7565 - val_categorical_accuracy: 0.7860 - 538ms/epoch - 11ms/step
Epoch 1288/1500
51/51 - 1s - loss: 0.0941 - categorical_accuracy: 0.9646 - val_loss: 2.0207 - val_categorical_accuracy: 0.7906 - 547ms/epoch - 11ms/step
Epoch 1289/1500
51/51 - 1s - loss: 0.0613 - categorical_accuracy: 0.9767 - val_loss: 2.1751 - val_categorical_accuracy: 0.7920 - 548ms/epoch - 11ms/step
Epoch 1290/1500
51/51 - 1s - loss: 0.0571 - categorical_accuracy: 0.9782 - val_loss: 2.2084 - val_categorical_accuracy: 0.7925 - 535ms/epoch - 10ms/step
Epoch 1291/1500
51/51 - 1s - loss: 0.0536 - categorical_accuracy: 0.9804 - val_loss: 2.2855 - val_categorical_accuracy: 0.7900 - 549ms/epoch - 11ms/step
Epoch 1292/1500
51/51 - 1s - loss: 0.0592 - categorical_accuracy: 0.9773 - val_loss: 2.3698 - val_categorical_accuracy: 0.7906 - 520ms/epoch - 10ms/step
Epoch 1293/1500
51/51 - 1s - loss: 0.0569 - categorical_accuracy: 0.9792 - val_loss: 2.3133 - val_categorical_accuracy: 0.7870 - 566ms/epoch - 11ms/step
Epoch 1294/1500
51/51 - 1s - loss: 0.0567 - categorical_accuracy: 0.9780 - val_loss: 2.3431 - val_categorical_accuracy: 0.7865 - 530ms/epoch - 10ms/step
Epoch 1295/1500
51/51 - 1s - loss: 0.0536 - categorical_accuracy: 0.9792 - val_loss: 2.3545 - val_categorical_accuracy: 0.7727 - 559ms/epoch - 11ms/step
Epoch 1296/1500
51/51 - 1s - loss: 0.0508 - categorical_accuracy: 0.9800 - val_loss: 2.3461 - val_categorical_accuracy: 0.7901 - 521ms/epoch - 10ms/step
Epoch 1297/1500
51/51 - 1s - loss: 0.0515 - categorical_accuracy: 0.9797 - val_loss: 2.3999 - val_categorical_accuracy: 0.7869 - 553ms/epoch - 11ms/step
Epoch 1298/1500
51/51 - 1s - loss: 0.0556 - categorical_accuracy: 0.9782 - val_loss: 2.4186 - val_categorical_accuracy: 0.7904 - 534ms/epoch - 10ms/step
Epoch 1299/1500
51/51 - 1s - loss: 0.0540 - categorical_accuracy: 0.9794 - val_loss: 2.4023 - val_categorical_accuracy: 0.7887 - 573ms/epoch - 11ms/step
Epoch 1300/1500
51/51 - 1s - loss: 0.0516 - categorical_accuracy: 0.9794 - val_loss: 2.3774 - val_categorical_accuracy: 0.7883 - 542ms/epoch - 11ms/step
Epoch 1301/1500
51/51 - 1s - loss: 0.0563 - categorical_accuracy: 0.9786 - val_loss: 2.6538 - val_categorical_accuracy: 0.7443 - 535ms/epoch - 10ms/step
Epoch 1302/1500
51/51 - 1s - loss: 0.3303 - categorical_accuracy: 0.9202 - val_loss: 2.0365 - val_categorical_accuracy: 0.7865 - 545ms/epoch - 11ms/step
Epoch 1303/1500
51/51 - 1s - loss: 0.0662 - categorical_accuracy: 0.9745 - val_loss: 2.2793 - val_categorical_accuracy: 0.7936 - 520ms/epoch - 10ms/step
Epoch 1304/1500
51/51 - 1s - loss: 0.0588 - categorical_accuracy: 0.9780 - val_loss: 2.2225 - val_categorical_accuracy: 0.7792 - 569ms/epoch - 11ms/step
Epoch 1305/1500
51/51 - 1s - loss: 0.0569 - categorical_accuracy: 0.9779 - val_loss: 2.3091 - val_categorical_accuracy: 0.7909 - 516ms/epoch - 10ms/step
Epoch 1306/1500
51/51 - 1s - loss: 0.0511 - categorical_accuracy: 0.9803 - val_loss: 2.2898 - val_categorical_accuracy: 0.7886 - 519ms/epoch - 10ms/step
Epoch 1307/1500
51/51 - 0s - loss: 0.0513 - categorical_accuracy: 0.9799 - val_loss: 2.3593 - val_categorical_accuracy: 0.7836 - 490ms/epoch - 10ms/step
Epoch 1308/1500
51/51 - 1s - loss: 0.0535 - categorical_accuracy: 0.9789 - val_loss: 2.3179 - val_categorical_accuracy: 0.7871 - 510ms/epoch - 10ms/step
Epoch 1309/1500
51/51 - 0s - loss: 0.0514 - categorical_accuracy: 0.9794 - val_loss: 2.3938 - val_categorical_accuracy: 0.7907 - 483ms/epoch - 9ms/step
Epoch 1310/1500
51/51 - 1s - loss: 0.0506 - categorical_accuracy: 0.9811 - val_loss: 2.4019 - val_categorical_accuracy: 0.7922 - 532ms/epoch - 10ms/step
Epoch 1311/1500
51/51 - 0s - loss: 0.0518 - categorical_accuracy: 0.9804 - val_loss: 2.4931 - val_categorical_accuracy: 0.7774 - 489ms/epoch - 10ms/step
Epoch 1312/1500
51/51 - 1s - loss: 0.0560 - categorical_accuracy: 0.9780 - val_loss: 2.4511 - val_categorical_accuracy: 0.7768 - 503ms/epoch - 10ms/step
Epoch 1313/1500
51/51 - 0s - loss: 0.0567 - categorical_accuracy: 0.9787 - val_loss: 2.4422 - val_categorical_accuracy: 0.7877 - 488ms/epoch - 10ms/step
Epoch 1314/1500
51/51 - 1s - loss: 0.0500 - categorical_accuracy: 0.9811 - val_loss: 2.4533 - val_categorical_accuracy: 0.7844 - 523ms/epoch - 10ms/step
Epoch 1315/1500
51/51 - 0s - loss: 0.0523 - categorical_accuracy: 0.9797 - val_loss: 2.5083 - val_categorical_accuracy: 0.7917 - 473ms/epoch - 9ms/step
Epoch 1316/1500
51/51 - 1s - loss: 0.0520 - categorical_accuracy: 0.9800 - val_loss: 2.4660 - val_categorical_accuracy: 0.7840 - 518ms/epoch - 10ms/step
Epoch 1317/1500
51/51 - 0s - loss: 0.0509 - categorical_accuracy: 0.9804 - val_loss: 2.5041 - val_categorical_accuracy: 0.7927 - 478ms/epoch - 9ms/step
Epoch 1318/1500
51/51 - 1s - loss: 0.1129 - categorical_accuracy: 0.9612 - val_loss: 2.4450 - val_categorical_accuracy: 0.7860 - 541ms/epoch - 11ms/step
Epoch 1319/1500
51/51 - 0s - loss: 0.0645 - categorical_accuracy: 0.9748 - val_loss: 2.5700 - val_categorical_accuracy: 0.7789 - 491ms/epoch - 10ms/step
Epoch 1320/1500
51/51 - 1s - loss: 0.2629 - categorical_accuracy: 0.9327 - val_loss: 2.1498 - val_categorical_accuracy: 0.7825 - 509ms/epoch - 10ms/step
Epoch 1321/1500
51/51 - 0s - loss: 0.0749 - categorical_accuracy: 0.9711 - val_loss: 2.2011 - val_categorical_accuracy: 0.7903 - 485ms/epoch - 10ms/step
Epoch 1322/1500
51/51 - 1s - loss: 0.0603 - categorical_accuracy: 0.9772 - val_loss: 2.2459 - val_categorical_accuracy: 0.7947 - 518ms/epoch - 10ms/step
Epoch 1323/1500
51/51 - 0s - loss: 0.0546 - categorical_accuracy: 0.9799 - val_loss: 2.2929 - val_categorical_accuracy: 0.7880 - 495ms/epoch - 10ms/step
Epoch 1324/1500
51/51 - 1s - loss: 0.0555 - categorical_accuracy: 0.9782 - val_loss: 2.3191 - val_categorical_accuracy: 0.7869 - 510ms/epoch - 10ms/step
Epoch 1325/1500
51/51 - 0s - loss: 0.0524 - categorical_accuracy: 0.9796 - val_loss: 2.3571 - val_categorical_accuracy: 0.7903 - 495ms/epoch - 10ms/step
Epoch 1326/1500
51/51 - 1s - loss: 0.0596 - categorical_accuracy: 0.9777 - val_loss: 2.3652 - val_categorical_accuracy: 0.7923 - 509ms/epoch - 10ms/step
Epoch 1327/1500
51/51 - 0s - loss: 0.0532 - categorical_accuracy: 0.9794 - val_loss: 2.3502 - val_categorical_accuracy: 0.7879 - 484ms/epoch - 9ms/step
Epoch 1328/1500
51/51 - 1s - loss: 0.0515 - categorical_accuracy: 0.9802 - val_loss: 2.4271 - val_categorical_accuracy: 0.7896 - 508ms/epoch - 10ms/step
Epoch 1329/1500
51/51 - 0s - loss: 0.0539 - categorical_accuracy: 0.9796 - val_loss: 2.4547 - val_categorical_accuracy: 0.7910 - 490ms/epoch - 10ms/step
Epoch 1330/1500
51/51 - 1s - loss: 0.0494 - categorical_accuracy: 0.9814 - val_loss: 2.4474 - val_categorical_accuracy: 0.7837 - 540ms/epoch - 11ms/step
Epoch 1331/1500
51/51 - 0s - loss: 0.0488 - categorical_accuracy: 0.9811 - val_loss: 2.4450 - val_categorical_accuracy: 0.7883 - 485ms/epoch - 10ms/step
Epoch 1332/1500
51/51 - 1s - loss: 0.0534 - categorical_accuracy: 0.9789 - val_loss: 2.4370 - val_categorical_accuracy: 0.7800 - 521ms/epoch - 10ms/step
Epoch 1333/1500
51/51 - 0s - loss: 0.0579 - categorical_accuracy: 0.9784 - val_loss: 2.4160 - val_categorical_accuracy: 0.7830 - 489ms/epoch - 10ms/step
Epoch 1334/1500
51/51 - 0s - loss: 0.0619 - categorical_accuracy: 0.9767 - val_loss: 2.3935 - val_categorical_accuracy: 0.7880 - 495ms/epoch - 10ms/step
Epoch 1335/1500
51/51 - 1s - loss: 0.0620 - categorical_accuracy: 0.9767 - val_loss: 2.4140 - val_categorical_accuracy: 0.7843 - 500ms/epoch - 10ms/step
Epoch 1336/1500
51/51 - 1s - loss: 0.0527 - categorical_accuracy: 0.9797 - val_loss: 2.4474 - val_categorical_accuracy: 0.7863 - 506ms/epoch - 10ms/step
Epoch 1337/1500
51/51 - 0s - loss: 0.0516 - categorical_accuracy: 0.9799 - val_loss: 2.5389 - val_categorical_accuracy: 0.7807 - 491ms/epoch - 10ms/step
Epoch 1338/1500
51/51 - 1s - loss: 0.0507 - categorical_accuracy: 0.9806 - val_loss: 2.4784 - val_categorical_accuracy: 0.7809 - 527ms/epoch - 10ms/step
Epoch 1339/1500
51/51 - 1s - loss: 0.1511 - categorical_accuracy: 0.9517 - val_loss: 5.1405 - val_categorical_accuracy: 0.4088 - 500ms/epoch - 10ms/step
Epoch 1340/1500
51/51 - 0s - loss: 0.7109 - categorical_accuracy: 0.8339 - val_loss: 1.4655 - val_categorical_accuracy: 0.7635 - 494ms/epoch - 10ms/step
Epoch 1341/1500
51/51 - 0s - loss: 0.1410 - categorical_accuracy: 0.9481 - val_loss: 1.8259 - val_categorical_accuracy: 0.7876 - 498ms/epoch - 10ms/step
Epoch 1342/1500
51/51 - 1s - loss: 0.0793 - categorical_accuracy: 0.9712 - val_loss: 1.9883 - val_categorical_accuracy: 0.7865 - 504ms/epoch - 10ms/step
Epoch 1343/1500
51/51 - 0s - loss: 0.0601 - categorical_accuracy: 0.9788 - val_loss: 2.0759 - val_categorical_accuracy: 0.7924 - 487ms/epoch - 10ms/step
Epoch 1344/1500
51/51 - 1s - loss: 0.0564 - categorical_accuracy: 0.9787 - val_loss: 2.0951 - val_categorical_accuracy: 0.7847 - 522ms/epoch - 10ms/step
Epoch 1345/1500
51/51 - 0s - loss: 0.0559 - categorical_accuracy: 0.9782 - val_loss: 2.1792 - val_categorical_accuracy: 0.7867 - 481ms/epoch - 9ms/step
Epoch 1346/1500
51/51 - 1s - loss: 0.0512 - categorical_accuracy: 0.9804 - val_loss: 2.2573 - val_categorical_accuracy: 0.7785 - 503ms/epoch - 10ms/step
Epoch 1347/1500
51/51 - 1s - loss: 0.0550 - categorical_accuracy: 0.9789 - val_loss: 2.2218 - val_categorical_accuracy: 0.7887 - 504ms/epoch - 10ms/step
Epoch 1348/1500
51/51 - 1s - loss: 0.0542 - categorical_accuracy: 0.9798 - val_loss: 2.2580 - val_categorical_accuracy: 0.7823 - 534ms/epoch - 10ms/step
Epoch 1349/1500
51/51 - 1s - loss: 0.0548 - categorical_accuracy: 0.9785 - val_loss: 2.2774 - val_categorical_accuracy: 0.7896 - 541ms/epoch - 11ms/step
Epoch 1350/1500
51/51 - 1s - loss: 0.0510 - categorical_accuracy: 0.9800 - val_loss: 2.3033 - val_categorical_accuracy: 0.7904 - 542ms/epoch - 11ms/step
Epoch 1351/1500
51/51 - 1s - loss: 0.0504 - categorical_accuracy: 0.9806 - val_loss: 2.3757 - val_categorical_accuracy: 0.7925 - 531ms/epoch - 10ms/step
Epoch 1352/1500
51/51 - 1s - loss: 0.0497 - categorical_accuracy: 0.9811 - val_loss: 2.3447 - val_categorical_accuracy: 0.7775 - 798ms/epoch - 16ms/step
Epoch 1353/1500
51/51 - 1s - loss: 0.0528 - categorical_accuracy: 0.9797 - val_loss: 2.4238 - val_categorical_accuracy: 0.7922 - 590ms/epoch - 12ms/step
Epoch 1354/1500
51/51 - 1s - loss: 0.0572 - categorical_accuracy: 0.9780 - val_loss: 2.3468 - val_categorical_accuracy: 0.7865 - 542ms/epoch - 11ms/step
Epoch 1355/1500
51/51 - 1s - loss: 0.0528 - categorical_accuracy: 0.9802 - val_loss: 2.4459 - val_categorical_accuracy: 0.7940 - 564ms/epoch - 11ms/step
Epoch 1356/1500
51/51 - 1s - loss: 0.0546 - categorical_accuracy: 0.9794 - val_loss: 2.3837 - val_categorical_accuracy: 0.7872 - 573ms/epoch - 11ms/step
Epoch 1357/1500
51/51 - 1s - loss: 0.0506 - categorical_accuracy: 0.9802 - val_loss: 2.3955 - val_categorical_accuracy: 0.7925 - 561ms/epoch - 11ms/step
Epoch 1358/1500
51/51 - 1s - loss: 0.0526 - categorical_accuracy: 0.9794 - val_loss: 2.4407 - val_categorical_accuracy: 0.7881 - 601ms/epoch - 12ms/step
Epoch 1359/1500
51/51 - 1s - loss: 0.0541 - categorical_accuracy: 0.9789 - val_loss: 2.4124 - val_categorical_accuracy: 0.7894 - 552ms/epoch - 11ms/step
Epoch 1360/1500
51/51 - 1s - loss: 0.0516 - categorical_accuracy: 0.9801 - val_loss: 2.5140 - val_categorical_accuracy: 0.7899 - 559ms/epoch - 11ms/step
Epoch 1361/1500
51/51 - 1s - loss: 0.0520 - categorical_accuracy: 0.9801 - val_loss: 2.4095 - val_categorical_accuracy: 0.7857 - 552ms/epoch - 11ms/step
Epoch 1362/1500
51/51 - 1s - loss: 0.0524 - categorical_accuracy: 0.9801 - val_loss: 2.4483 - val_categorical_accuracy: 0.7931 - 554ms/epoch - 11ms/step
Epoch 1363/1500
51/51 - 1s - loss: 0.0535 - categorical_accuracy: 0.9795 - val_loss: 2.5032 - val_categorical_accuracy: 0.7899 - 561ms/epoch - 11ms/step
Epoch 1364/1500
51/51 - 1s - loss: 0.0502 - categorical_accuracy: 0.9804 - val_loss: 2.5006 - val_categorical_accuracy: 0.7900 - 558ms/epoch - 11ms/step
Epoch 1365/1500
51/51 - 1s - loss: 0.0494 - categorical_accuracy: 0.9816 - val_loss: 2.5350 - val_categorical_accuracy: 0.7861 - 587ms/epoch - 12ms/step
Epoch 1366/1500
51/51 - 1s - loss: 0.0498 - categorical_accuracy: 0.9809 - val_loss: 2.6444 - val_categorical_accuracy: 0.7812 - 525ms/epoch - 10ms/step
Epoch 1367/1500
51/51 - 1s - loss: 0.0546 - categorical_accuracy: 0.9792 - val_loss: 2.5095 - val_categorical_accuracy: 0.7791 - 582ms/epoch - 11ms/step
Epoch 1368/1500
51/51 - 1s - loss: 0.0564 - categorical_accuracy: 0.9779 - val_loss: 2.5075 - val_categorical_accuracy: 0.7860 - 536ms/epoch - 11ms/step
Epoch 1369/1500
51/51 - 1s - loss: 0.0571 - categorical_accuracy: 0.9780 - val_loss: 2.5399 - val_categorical_accuracy: 0.7900 - 563ms/epoch - 11ms/step
Epoch 1370/1500
51/51 - 1s - loss: 0.0502 - categorical_accuracy: 0.9808 - val_loss: 2.5674 - val_categorical_accuracy: 0.7938 - 558ms/epoch - 11ms/step
Epoch 1371/1500
51/51 - 1s - loss: 0.0746 - categorical_accuracy: 0.9720 - val_loss: 2.4920 - val_categorical_accuracy: 0.7898 - 571ms/epoch - 11ms/step
Epoch 1372/1500
51/51 - 1s - loss: 0.0500 - categorical_accuracy: 0.9804 - val_loss: 2.5151 - val_categorical_accuracy: 0.7882 - 571ms/epoch - 11ms/step
Epoch 1373/1500
51/51 - 1s - loss: 0.0499 - categorical_accuracy: 0.9804 - val_loss: 2.5432 - val_categorical_accuracy: 0.7821 - 535ms/epoch - 10ms/step
Epoch 1374/1500
51/51 - 1s - loss: 0.0590 - categorical_accuracy: 0.9772 - val_loss: 2.5413 - val_categorical_accuracy: 0.7850 - 588ms/epoch - 12ms/step
Epoch 1375/1500
51/51 - 1s - loss: 0.0525 - categorical_accuracy: 0.9799 - val_loss: 2.5013 - val_categorical_accuracy: 0.7807 - 550ms/epoch - 11ms/step
Epoch 1376/1500
51/51 - 1s - loss: 0.0494 - categorical_accuracy: 0.9811 - val_loss: 2.5529 - val_categorical_accuracy: 0.7883 - 570ms/epoch - 11ms/step
Epoch 1377/1500
51/51 - 1s - loss: 0.0464 - categorical_accuracy: 0.9819 - val_loss: 2.6032 - val_categorical_accuracy: 0.7914 - 553ms/epoch - 11ms/step
Epoch 1378/1500
51/51 - 1s - loss: 0.6564 - categorical_accuracy: 0.8921 - val_loss: 0.8791 - val_categorical_accuracy: 0.7668 - 549ms/epoch - 11ms/step
Epoch 1379/1500
51/51 - 1s - loss: 0.7220 - categorical_accuracy: 0.7846 - val_loss: 0.8332 - val_categorical_accuracy: 0.7717 - 554ms/epoch - 11ms/step
Epoch 1380/1500
51/51 - 1s - loss: 0.5281 - categorical_accuracy: 0.8243 - val_loss: 0.9870 - val_categorical_accuracy: 0.7813 - 569ms/epoch - 11ms/step
Epoch 1381/1500
51/51 - 1s - loss: 0.3463 - categorical_accuracy: 0.8796 - val_loss: 1.1675 - val_categorical_accuracy: 0.7796 - 603ms/epoch - 12ms/step
Epoch 1382/1500
51/51 - 1s - loss: 0.2243 - categorical_accuracy: 0.9201 - val_loss: 1.4616 - val_categorical_accuracy: 0.7887 - 573ms/epoch - 11ms/step
Epoch 1383/1500
51/51 - 1s - loss: 0.1559 - categorical_accuracy: 0.9417 - val_loss: 1.6922 - val_categorical_accuracy: 0.7774 - 587ms/epoch - 12ms/step
Epoch 1384/1500
51/51 - 1s - loss: 0.1169 - categorical_accuracy: 0.9567 - val_loss: 1.7540 - val_categorical_accuracy: 0.7798 - 555ms/epoch - 11ms/step
Epoch 1385/1500
51/51 - 1s - loss: 0.0963 - categorical_accuracy: 0.9632 - val_loss: 1.9017 - val_categorical_accuracy: 0.7816 - 538ms/epoch - 11ms/step
Epoch 1386/1500
51/51 - 1s - loss: 0.0821 - categorical_accuracy: 0.9699 - val_loss: 1.9573 - val_categorical_accuracy: 0.7863 - 562ms/epoch - 11ms/step
Epoch 1387/1500
51/51 - 1s - loss: 0.0769 - categorical_accuracy: 0.9717 - val_loss: 2.0130 - val_categorical_accuracy: 0.7876 - 556ms/epoch - 11ms/step
Epoch 1388/1500
51/51 - 1s - loss: 0.0732 - categorical_accuracy: 0.9738 - val_loss: 2.1083 - val_categorical_accuracy: 0.7888 - 576ms/epoch - 11ms/step
Epoch 1389/1500
51/51 - 1s - loss: 0.0674 - categorical_accuracy: 0.9748 - val_loss: 2.1412 - val_categorical_accuracy: 0.7916 - 542ms/epoch - 11ms/step
Epoch 1390/1500
51/51 - 1s - loss: 0.0637 - categorical_accuracy: 0.9767 - val_loss: 2.1703 - val_categorical_accuracy: 0.7897 - 559ms/epoch - 11ms/step
Epoch 1391/1500
51/51 - 1s - loss: 0.0661 - categorical_accuracy: 0.9749 - val_loss: 2.2987 - val_categorical_accuracy: 0.7897 - 533ms/epoch - 10ms/step
Epoch 1392/1500
51/51 - 1s - loss: 0.1198 - categorical_accuracy: 0.9583 - val_loss: 2.1692 - val_categorical_accuracy: 0.7896 - 580ms/epoch - 11ms/step
Epoch 1393/1500
51/51 - 1s - loss: 0.0661 - categorical_accuracy: 0.9751 - val_loss: 2.1930 - val_categorical_accuracy: 0.7919 - 554ms/epoch - 11ms/step
Epoch 1394/1500
51/51 - 1s - loss: 0.0663 - categorical_accuracy: 0.9743 - val_loss: 2.2606 - val_categorical_accuracy: 0.7954 - 562ms/epoch - 11ms/step
Epoch 1395/1500
51/51 - 1s - loss: 0.0629 - categorical_accuracy: 0.9752 - val_loss: 2.2137 - val_categorical_accuracy: 0.7872 - 568ms/epoch - 11ms/step
Epoch 1396/1500
51/51 - 1s - loss: 0.0649 - categorical_accuracy: 0.9750 - val_loss: 2.2861 - val_categorical_accuracy: 0.7898 - 531ms/epoch - 10ms/step
Epoch 1397/1500
51/51 - 1s - loss: 0.0603 - categorical_accuracy: 0.9772 - val_loss: 2.2944 - val_categorical_accuracy: 0.7846 - 596ms/epoch - 12ms/step
Epoch 1398/1500
51/51 - 1s - loss: 0.0603 - categorical_accuracy: 0.9768 - val_loss: 2.2344 - val_categorical_accuracy: 0.7836 - 553ms/epoch - 11ms/step
Epoch 1399/1500
51/51 - 1s - loss: 0.0561 - categorical_accuracy: 0.9789 - val_loss: 2.3316 - val_categorical_accuracy: 0.7900 - 581ms/epoch - 11ms/step
Epoch 1400/1500
51/51 - 1s - loss: 0.0548 - categorical_accuracy: 0.9786 - val_loss: 2.3352 - val_categorical_accuracy: 0.7899 - 549ms/epoch - 11ms/step
Epoch 1401/1500
51/51 - 1s - loss: 0.0592 - categorical_accuracy: 0.9777 - val_loss: 2.4033 - val_categorical_accuracy: 0.7964 - 543ms/epoch - 11ms/step
Epoch 1402/1500
51/51 - 1s - loss: 0.0645 - categorical_accuracy: 0.9753 - val_loss: 2.3763 - val_categorical_accuracy: 0.7800 - 577ms/epoch - 11ms/step
Epoch 1403/1500
51/51 - 1s - loss: 0.0585 - categorical_accuracy: 0.9779 - val_loss: 2.4068 - val_categorical_accuracy: 0.7880 - 557ms/epoch - 11ms/step
Epoch 1404/1500
51/51 - 1s - loss: 0.0569 - categorical_accuracy: 0.9778 - val_loss: 2.4447 - val_categorical_accuracy: 0.7942 - 573ms/epoch - 11ms/step
Epoch 1405/1500
51/51 - 1s - loss: 0.0611 - categorical_accuracy: 0.9772 - val_loss: 2.3973 - val_categorical_accuracy: 0.7858 - 537ms/epoch - 11ms/step
Epoch 1406/1500
51/51 - 1s - loss: 0.0605 - categorical_accuracy: 0.9769 - val_loss: 2.3718 - val_categorical_accuracy: 0.7919 - 588ms/epoch - 12ms/step
Epoch 1407/1500
51/51 - 1s - loss: 0.0540 - categorical_accuracy: 0.9797 - val_loss: 2.4694 - val_categorical_accuracy: 0.7883 - 518ms/epoch - 10ms/step
Epoch 1408/1500
51/51 - 1s - loss: 0.0554 - categorical_accuracy: 0.9789 - val_loss: 2.6497 - val_categorical_accuracy: 0.7918 - 560ms/epoch - 11ms/step
Epoch 1409/1500
51/51 - 1s - loss: 0.0722 - categorical_accuracy: 0.9731 - val_loss: 2.3822 - val_categorical_accuracy: 0.7828 - 564ms/epoch - 11ms/step
Epoch 1410/1500
51/51 - 1s - loss: 0.0617 - categorical_accuracy: 0.9767 - val_loss: 2.4137 - val_categorical_accuracy: 0.7752 - 582ms/epoch - 11ms/step
Epoch 1411/1500
51/51 - 1s - loss: 0.0605 - categorical_accuracy: 0.9758 - val_loss: 2.4170 - val_categorical_accuracy: 0.7851 - 569ms/epoch - 11ms/step
Epoch 1412/1500
51/51 - 1s - loss: 0.0594 - categorical_accuracy: 0.9770 - val_loss: 2.3935 - val_categorical_accuracy: 0.7860 - 519ms/epoch - 10ms/step
Epoch 1413/1500
51/51 - 1s - loss: 0.0539 - categorical_accuracy: 0.9799 - val_loss: 2.5009 - val_categorical_accuracy: 0.7887 - 533ms/epoch - 10ms/step
Epoch 1414/1500
51/51 - 1s - loss: 0.0562 - categorical_accuracy: 0.9779 - val_loss: 2.4417 - val_categorical_accuracy: 0.7889 - 509ms/epoch - 10ms/step
Epoch 1415/1500
51/51 - 1s - loss: 0.0561 - categorical_accuracy: 0.9790 - val_loss: 2.5566 - val_categorical_accuracy: 0.7782 - 529ms/epoch - 10ms/step
Epoch 1416/1500
51/51 - 1s - loss: 0.1020 - categorical_accuracy: 0.9635 - val_loss: 2.4067 - val_categorical_accuracy: 0.7723 - 504ms/epoch - 10ms/step
Epoch 1417/1500
51/51 - 1s - loss: 0.0664 - categorical_accuracy: 0.9742 - val_loss: 2.3929 - val_categorical_accuracy: 0.7857 - 535ms/epoch - 10ms/step
Epoch 1418/1500
51/51 - 0s - loss: 0.0594 - categorical_accuracy: 0.9769 - val_loss: 2.4847 - val_categorical_accuracy: 0.7907 - 499ms/epoch - 10ms/step
Epoch 1419/1500
51/51 - 1s - loss: 0.0581 - categorical_accuracy: 0.9775 - val_loss: 2.5072 - val_categorical_accuracy: 0.7906 - 516ms/epoch - 10ms/step
Epoch 1420/1500
51/51 - 0s - loss: 0.0560 - categorical_accuracy: 0.9783 - val_loss: 2.4569 - val_categorical_accuracy: 0.7887 - 499ms/epoch - 10ms/step
Epoch 1421/1500
51/51 - 1s - loss: 0.0626 - categorical_accuracy: 0.9760 - val_loss: 2.4800 - val_categorical_accuracy: 0.7901 - 533ms/epoch - 10ms/step
Epoch 1422/1500
51/51 - 1s - loss: 0.0567 - categorical_accuracy: 0.9777 - val_loss: 2.5195 - val_categorical_accuracy: 0.7851 - 507ms/epoch - 10ms/step
Epoch 1423/1500
51/51 - 1s - loss: 0.0546 - categorical_accuracy: 0.9790 - val_loss: 2.4770 - val_categorical_accuracy: 0.7893 - 530ms/epoch - 10ms/step
Epoch 1424/1500
51/51 - 0s - loss: 0.0605 - categorical_accuracy: 0.9763 - val_loss: 2.5718 - val_categorical_accuracy: 0.7865 - 489ms/epoch - 10ms/step
Epoch 1425/1500
51/51 - 1s - loss: 0.0701 - categorical_accuracy: 0.9738 - val_loss: 2.4572 - val_categorical_accuracy: 0.7872 - 542ms/epoch - 11ms/step
Epoch 1426/1500
51/51 - 1s - loss: 0.0640 - categorical_accuracy: 0.9765 - val_loss: 2.4666 - val_categorical_accuracy: 0.7889 - 561ms/epoch - 11ms/step
Epoch 1427/1500
51/51 - 1s - loss: 0.0527 - categorical_accuracy: 0.9799 - val_loss: 2.4672 - val_categorical_accuracy: 0.7873 - 529ms/epoch - 10ms/step
Epoch 1428/1500
51/51 - 1s - loss: 0.0561 - categorical_accuracy: 0.9785 - val_loss: 2.5092 - val_categorical_accuracy: 0.7864 - 601ms/epoch - 12ms/step
Epoch 1429/1500
51/51 - 1s - loss: 0.0544 - categorical_accuracy: 0.9794 - val_loss: 2.4848 - val_categorical_accuracy: 0.7765 - 547ms/epoch - 11ms/step
Epoch 1430/1500
51/51 - 1s - loss: 0.3072 - categorical_accuracy: 0.9242 - val_loss: 2.1495 - val_categorical_accuracy: 0.7779 - 530ms/epoch - 10ms/step
Epoch 1431/1500
51/51 - 1s - loss: 0.0651 - categorical_accuracy: 0.9758 - val_loss: 2.1883 - val_categorical_accuracy: 0.7858 - 532ms/epoch - 10ms/step
Epoch 1432/1500
51/51 - 1s - loss: 0.0516 - categorical_accuracy: 0.9809 - val_loss: 2.2705 - val_categorical_accuracy: 0.7921 - 533ms/epoch - 10ms/step
Epoch 1433/1500
51/51 - 1s - loss: 0.0524 - categorical_accuracy: 0.9797 - val_loss: 2.3569 - val_categorical_accuracy: 0.7913 - 512ms/epoch - 10ms/step
Epoch 1434/1500
51/51 - 1s - loss: 0.0496 - categorical_accuracy: 0.9814 - val_loss: 2.3849 - val_categorical_accuracy: 0.7932 - 534ms/epoch - 10ms/step
Epoch 1435/1500
51/51 - 1s - loss: 0.0522 - categorical_accuracy: 0.9792 - val_loss: 2.3645 - val_categorical_accuracy: 0.7881 - 501ms/epoch - 10ms/step
Epoch 1436/1500
51/51 - 1s - loss: 0.0517 - categorical_accuracy: 0.9813 - val_loss: 2.3813 - val_categorical_accuracy: 0.7853 - 535ms/epoch - 10ms/step
Epoch 1437/1500
51/51 - 1s - loss: 0.0567 - categorical_accuracy: 0.9787 - val_loss: 2.4656 - val_categorical_accuracy: 0.7755 - 516ms/epoch - 10ms/step
Epoch 1438/1500
51/51 - 1s - loss: 0.0531 - categorical_accuracy: 0.9792 - val_loss: 2.4849 - val_categorical_accuracy: 0.7899 - 526ms/epoch - 10ms/step
Epoch 1439/1500
51/51 - 1s - loss: 0.0493 - categorical_accuracy: 0.9812 - val_loss: 2.5373 - val_categorical_accuracy: 0.7838 - 549ms/epoch - 11ms/step
Epoch 1440/1500
51/51 - 1s - loss: 0.0551 - categorical_accuracy: 0.9785 - val_loss: 2.4851 - val_categorical_accuracy: 0.7956 - 525ms/epoch - 10ms/step
Epoch 1441/1500
51/51 - 1s - loss: 0.0535 - categorical_accuracy: 0.9797 - val_loss: 2.4382 - val_categorical_accuracy: 0.7815 - 531ms/epoch - 10ms/step
Epoch 1442/1500
51/51 - 1s - loss: 0.0533 - categorical_accuracy: 0.9799 - val_loss: 2.4999 - val_categorical_accuracy: 0.7906 - 612ms/epoch - 12ms/step
Epoch 1443/1500
51/51 - 1s - loss: 0.0530 - categorical_accuracy: 0.9793 - val_loss: 2.4850 - val_categorical_accuracy: 0.7898 - 585ms/epoch - 11ms/step
Epoch 1444/1500
51/51 - 1s - loss: 0.0551 - categorical_accuracy: 0.9790 - val_loss: 2.5024 - val_categorical_accuracy: 0.7777 - 540ms/epoch - 11ms/step
Epoch 1445/1500
51/51 - 1s - loss: 0.0554 - categorical_accuracy: 0.9787 - val_loss: 2.5181 - val_categorical_accuracy: 0.7865 - 524ms/epoch - 10ms/step
Epoch 1446/1500
51/51 - 1s - loss: 0.0534 - categorical_accuracy: 0.9796 - val_loss: 2.5061 - val_categorical_accuracy: 0.7831 - 554ms/epoch - 11ms/step
Epoch 1447/1500
51/51 - 1s - loss: 0.0523 - categorical_accuracy: 0.9804 - val_loss: 2.5408 - val_categorical_accuracy: 0.7934 - 525ms/epoch - 10ms/step
Epoch 1448/1500
51/51 - 0s - loss: 0.0565 - categorical_accuracy: 0.9780 - val_loss: 2.6238 - val_categorical_accuracy: 0.7903 - 490ms/epoch - 10ms/step
Epoch 1449/1500
51/51 - 1s - loss: 0.0550 - categorical_accuracy: 0.9788 - val_loss: 2.5723 - val_categorical_accuracy: 0.7881 - 568ms/epoch - 11ms/step
Epoch 1450/1500
51/51 - 0s - loss: 0.0566 - categorical_accuracy: 0.9783 - val_loss: 2.5663 - val_categorical_accuracy: 0.7941 - 480ms/epoch - 9ms/step
Epoch 1451/1500
51/51 - 0s - loss: 0.2658 - categorical_accuracy: 0.9333 - val_loss: 1.8657 - val_categorical_accuracy: 0.7803 - 484ms/epoch - 9ms/step
Epoch 1452/1500
51/51 - 0s - loss: 0.0881 - categorical_accuracy: 0.9666 - val_loss: 2.2180 - val_categorical_accuracy: 0.7901 - 466ms/epoch - 9ms/step
Epoch 1453/1500
51/51 - 1s - loss: 0.0618 - categorical_accuracy: 0.9773 - val_loss: 2.2764 - val_categorical_accuracy: 0.7859 - 500ms/epoch - 10ms/step
Epoch 1454/1500
51/51 - 0s - loss: 0.0511 - categorical_accuracy: 0.9807 - val_loss: 2.3444 - val_categorical_accuracy: 0.7840 - 466ms/epoch - 9ms/step
Epoch 1455/1500
51/51 - 1s - loss: 0.0485 - categorical_accuracy: 0.9821 - val_loss: 2.3985 - val_categorical_accuracy: 0.7870 - 539ms/epoch - 11ms/step
Epoch 1456/1500
51/51 - 0s - loss: 0.0490 - categorical_accuracy: 0.9809 - val_loss: 2.4042 - val_categorical_accuracy: 0.7911 - 490ms/epoch - 10ms/step
Epoch 1457/1500
51/51 - 1s - loss: 0.0465 - categorical_accuracy: 0.9819 - val_loss: 2.4484 - val_categorical_accuracy: 0.7898 - 524ms/epoch - 10ms/step
Epoch 1458/1500
51/51 - 0s - loss: 0.0463 - categorical_accuracy: 0.9823 - val_loss: 2.4889 - val_categorical_accuracy: 0.7894 - 475ms/epoch - 9ms/step
Epoch 1459/1500
51/51 - 1s - loss: 0.0518 - categorical_accuracy: 0.9804 - val_loss: 2.5182 - val_categorical_accuracy: 0.7889 - 539ms/epoch - 11ms/step
Epoch 1460/1500
51/51 - 0s - loss: 0.0493 - categorical_accuracy: 0.9809 - val_loss: 2.4368 - val_categorical_accuracy: 0.7828 - 474ms/epoch - 9ms/step
Epoch 1461/1500
51/51 - 1s - loss: 0.0526 - categorical_accuracy: 0.9801 - val_loss: 2.4613 - val_categorical_accuracy: 0.7926 - 544ms/epoch - 11ms/step
Epoch 1462/1500
51/51 - 0s - loss: 0.0518 - categorical_accuracy: 0.9801 - val_loss: 2.5324 - val_categorical_accuracy: 0.7922 - 475ms/epoch - 9ms/step
Epoch 1463/1500
51/51 - 1s - loss: 0.0538 - categorical_accuracy: 0.9791 - val_loss: 2.4938 - val_categorical_accuracy: 0.7867 - 548ms/epoch - 11ms/step
Epoch 1464/1500
51/51 - 0s - loss: 0.0535 - categorical_accuracy: 0.9802 - val_loss: 2.5208 - val_categorical_accuracy: 0.7827 - 485ms/epoch - 10ms/step
Epoch 1465/1500
51/51 - 1s - loss: 0.0516 - categorical_accuracy: 0.9803 - val_loss: 2.5662 - val_categorical_accuracy: 0.7840 - 514ms/epoch - 10ms/step
Epoch 1466/1500
51/51 - 0s - loss: 0.0510 - categorical_accuracy: 0.9807 - val_loss: 2.6027 - val_categorical_accuracy: 0.7885 - 484ms/epoch - 9ms/step
Epoch 1467/1500
51/51 - 1s - loss: 0.0503 - categorical_accuracy: 0.9808 - val_loss: 2.5636 - val_categorical_accuracy: 0.7869 - 511ms/epoch - 10ms/step
Epoch 1468/1500
51/51 - 1s - loss: 0.0522 - categorical_accuracy: 0.9804 - val_loss: 2.5676 - val_categorical_accuracy: 0.7744 - 517ms/epoch - 10ms/step
Epoch 1469/1500
51/51 - 1s - loss: 0.0536 - categorical_accuracy: 0.9789 - val_loss: 2.5006 - val_categorical_accuracy: 0.7831 - 512ms/epoch - 10ms/step
Epoch 1470/1500
51/51 - 0s - loss: 0.0628 - categorical_accuracy: 0.9771 - val_loss: 2.5096 - val_categorical_accuracy: 0.7858 - 468ms/epoch - 9ms/step
Epoch 1471/1500
51/51 - 1s - loss: 0.0489 - categorical_accuracy: 0.9813 - val_loss: 2.5774 - val_categorical_accuracy: 0.7955 - 587ms/epoch - 12ms/step
Epoch 1472/1500
51/51 - 1s - loss: 0.0480 - categorical_accuracy: 0.9815 - val_loss: 2.5700 - val_categorical_accuracy: 0.7885 - 553ms/epoch - 11ms/step
Epoch 1473/1500
51/51 - 1s - loss: 0.0586 - categorical_accuracy: 0.9786 - val_loss: 2.6948 - val_categorical_accuracy: 0.7894 - 518ms/epoch - 10ms/step
Epoch 1474/1500
51/51 - 1s - loss: 0.3220 - categorical_accuracy: 0.9185 - val_loss: 2.0448 - val_categorical_accuracy: 0.7924 - 555ms/epoch - 11ms/step
Epoch 1475/1500
51/51 - 1s - loss: 0.0709 - categorical_accuracy: 0.9730 - val_loss: 2.2518 - val_categorical_accuracy: 0.7839 - 555ms/epoch - 11ms/step
Epoch 1476/1500
51/51 - 1s - loss: 0.0611 - categorical_accuracy: 0.9767 - val_loss: 2.2738 - val_categorical_accuracy: 0.7855 - 585ms/epoch - 11ms/step
Epoch 1477/1500
51/51 - 1s - loss: 0.0492 - categorical_accuracy: 0.9813 - val_loss: 2.3403 - val_categorical_accuracy: 0.7842 - 538ms/epoch - 11ms/step
Epoch 1478/1500
51/51 - 1s - loss: 0.0471 - categorical_accuracy: 0.9821 - val_loss: 2.4024 - val_categorical_accuracy: 0.7774 - 557ms/epoch - 11ms/step
Epoch 1479/1500
51/51 - 1s - loss: 0.0479 - categorical_accuracy: 0.9818 - val_loss: 2.4246 - val_categorical_accuracy: 0.7838 - 526ms/epoch - 10ms/step
Epoch 1480/1500
51/51 - 1s - loss: 0.0539 - categorical_accuracy: 0.9794 - val_loss: 2.4496 - val_categorical_accuracy: 0.7859 - 524ms/epoch - 10ms/step
Epoch 1481/1500
51/51 - 1s - loss: 0.0575 - categorical_accuracy: 0.9777 - val_loss: 2.4444 - val_categorical_accuracy: 0.7854 - 518ms/epoch - 10ms/step
Epoch 1482/1500
51/51 - 1s - loss: 0.0494 - categorical_accuracy: 0.9807 - val_loss: 2.4920 - val_categorical_accuracy: 0.7903 - 518ms/epoch - 10ms/step
Epoch 1483/1500
51/51 - 1s - loss: 0.0556 - categorical_accuracy: 0.9792 - val_loss: 2.5692 - val_categorical_accuracy: 0.7858 - 525ms/epoch - 10ms/step
Epoch 1484/1500
51/51 - 1s - loss: 0.0535 - categorical_accuracy: 0.9792 - val_loss: 2.5409 - val_categorical_accuracy: 0.7874 - 507ms/epoch - 10ms/step
Epoch 1485/1500
51/51 - 1s - loss: 0.0526 - categorical_accuracy: 0.9804 - val_loss: 2.4962 - val_categorical_accuracy: 0.7853 - 518ms/epoch - 10ms/step
Epoch 1486/1500
51/51 - 1s - loss: 0.0491 - categorical_accuracy: 0.9809 - val_loss: 2.5032 - val_categorical_accuracy: 0.7880 - 548ms/epoch - 11ms/step
Epoch 1487/1500
51/51 - 1s - loss: 0.0501 - categorical_accuracy: 0.9812 - val_loss: 2.5617 - val_categorical_accuracy: 0.7873 - 525ms/epoch - 10ms/step
Epoch 1488/1500
51/51 - 1s - loss: 0.0530 - categorical_accuracy: 0.9792 - val_loss: 2.5027 - val_categorical_accuracy: 0.7866 - 521ms/epoch - 10ms/step
Epoch 1489/1500
51/51 - 1s - loss: 0.0502 - categorical_accuracy: 0.9802 - val_loss: 2.5430 - val_categorical_accuracy: 0.7877 - 553ms/epoch - 11ms/step
Epoch 1490/1500
51/51 - 1s - loss: 0.0486 - categorical_accuracy: 0.9805 - val_loss: 2.5583 - val_categorical_accuracy: 0.7824 - 509ms/epoch - 10ms/step
Epoch 1491/1500
51/51 - 1s - loss: 0.0475 - categorical_accuracy: 0.9821 - val_loss: 2.5658 - val_categorical_accuracy: 0.7789 - 541ms/epoch - 11ms/step
Epoch 1492/1500
51/51 - 1s - loss: 0.0529 - categorical_accuracy: 0.9799 - val_loss: 2.5059 - val_categorical_accuracy: 0.7745 - 537ms/epoch - 11ms/step
Epoch 1493/1500
51/51 - 1s - loss: 0.0611 - categorical_accuracy: 0.9764 - val_loss: 2.5685 - val_categorical_accuracy: 0.7871 - 574ms/epoch - 11ms/step
Epoch 1494/1500
51/51 - 1s - loss: 0.2613 - categorical_accuracy: 0.9271 - val_loss: 2.1087 - val_categorical_accuracy: 0.7844 - 515ms/epoch - 10ms/step
Epoch 1495/1500
51/51 - 1s - loss: 0.0868 - categorical_accuracy: 0.9676 - val_loss: 2.2606 - val_categorical_accuracy: 0.7921 - 534ms/epoch - 10ms/step
Epoch 1496/1500
51/51 - 1s - loss: 0.0824 - categorical_accuracy: 0.9683 - val_loss: 2.4211 - val_categorical_accuracy: 0.7924 - 515ms/epoch - 10ms/step
Epoch 1497/1500
51/51 - 1s - loss: 0.1763 - categorical_accuracy: 0.9471 - val_loss: 2.1499 - val_categorical_accuracy: 0.7846 - 516ms/epoch - 10ms/step
Epoch 1498/1500
51/51 - 1s - loss: 0.0605 - categorical_accuracy: 0.9774 - val_loss: 2.2539 - val_categorical_accuracy: 0.7865 - 502ms/epoch - 10ms/step
Epoch 1499/1500
51/51 - 1s - loss: 0.0546 - categorical_accuracy: 0.9796 - val_loss: 2.2817 - val_categorical_accuracy: 0.7875 - 519ms/epoch - 10ms/step
Epoch 1500/1500
51/51 - 1s - loss: 0.0502 - categorical_accuracy: 0.9803 - val_loss: 2.3937 - val_categorical_accuracy: 0.7893 - 517ms/epoch - 10ms/step
processing fold # 2 
Epoch 1/1500
51/51 - 1s - loss: 0.9317 - categorical_accuracy: 0.7553 - val_loss: 0.8994 - val_categorical_accuracy: 0.7735 - 1s/epoch - 27ms/step
Epoch 2/1500
51/51 - 1s - loss: 0.8301 - categorical_accuracy: 0.7704 - val_loss: 0.8460 - val_categorical_accuracy: 0.7735 - 670ms/epoch - 13ms/step
Epoch 3/1500
51/51 - 1s - loss: 0.8160 - categorical_accuracy: 0.7704 - val_loss: 0.8082 - val_categorical_accuracy: 0.7735 - 551ms/epoch - 11ms/step
Epoch 4/1500
51/51 - 1s - loss: 0.8181 - categorical_accuracy: 0.7704 - val_loss: 0.8138 - val_categorical_accuracy: 0.7735 - 526ms/epoch - 10ms/step
Epoch 5/1500
51/51 - 1s - loss: 0.8161 - categorical_accuracy: 0.7704 - val_loss: 0.8060 - val_categorical_accuracy: 0.7735 - 588ms/epoch - 12ms/step
Epoch 6/1500
51/51 - 1s - loss: 0.8117 - categorical_accuracy: 0.7704 - val_loss: 0.7983 - val_categorical_accuracy: 0.7735 - 587ms/epoch - 12ms/step
Epoch 7/1500
51/51 - 1s - loss: 0.8057 - categorical_accuracy: 0.7704 - val_loss: 0.7971 - val_categorical_accuracy: 0.7735 - 570ms/epoch - 11ms/step
Epoch 8/1500
51/51 - 1s - loss: 0.8023 - categorical_accuracy: 0.7704 - val_loss: 0.7966 - val_categorical_accuracy: 0.7735 - 583ms/epoch - 11ms/step
Epoch 9/1500
51/51 - 1s - loss: 0.7981 - categorical_accuracy: 0.7704 - val_loss: 0.7944 - val_categorical_accuracy: 0.7735 - 507ms/epoch - 10ms/step
Epoch 10/1500
51/51 - 1s - loss: 0.7939 - categorical_accuracy: 0.7704 - val_loss: 0.7905 - val_categorical_accuracy: 0.7735 - 582ms/epoch - 11ms/step
Epoch 11/1500
51/51 - 1s - loss: 0.7938 - categorical_accuracy: 0.7704 - val_loss: 0.7898 - val_categorical_accuracy: 0.7735 - 531ms/epoch - 10ms/step
Epoch 12/1500
51/51 - 1s - loss: 0.7908 - categorical_accuracy: 0.7704 - val_loss: 0.7803 - val_categorical_accuracy: 0.7735 - 610ms/epoch - 12ms/step
Epoch 13/1500
51/51 - 1s - loss: 0.7843 - categorical_accuracy: 0.7704 - val_loss: 0.7788 - val_categorical_accuracy: 0.7735 - 589ms/epoch - 12ms/step
Epoch 14/1500
51/51 - 1s - loss: 0.7889 - categorical_accuracy: 0.7704 - val_loss: 0.7846 - val_categorical_accuracy: 0.7735 - 590ms/epoch - 12ms/step
Epoch 15/1500
51/51 - 1s - loss: 0.7779 - categorical_accuracy: 0.7704 - val_loss: 0.7713 - val_categorical_accuracy: 0.7735 - 633ms/epoch - 12ms/step
Epoch 16/1500
51/51 - 1s - loss: 0.7746 - categorical_accuracy: 0.7704 - val_loss: 0.7867 - val_categorical_accuracy: 0.7735 - 656ms/epoch - 13ms/step
Epoch 17/1500
51/51 - 1s - loss: 0.7749 - categorical_accuracy: 0.7704 - val_loss: 0.7946 - val_categorical_accuracy: 0.7735 - 595ms/epoch - 12ms/step
Epoch 18/1500
51/51 - 1s - loss: 0.7699 - categorical_accuracy: 0.7704 - val_loss: 0.7849 - val_categorical_accuracy: 0.7738 - 589ms/epoch - 12ms/step
Epoch 19/1500
51/51 - 1s - loss: 0.7614 - categorical_accuracy: 0.7705 - val_loss: 0.7567 - val_categorical_accuracy: 0.7735 - 553ms/epoch - 11ms/step
Epoch 20/1500
51/51 - 1s - loss: 0.7644 - categorical_accuracy: 0.7707 - val_loss: 0.7563 - val_categorical_accuracy: 0.7735 - 643ms/epoch - 13ms/step
Epoch 21/1500
51/51 - 1s - loss: 0.7543 - categorical_accuracy: 0.7706 - val_loss: 0.7644 - val_categorical_accuracy: 0.7735 - 609ms/epoch - 12ms/step
Epoch 22/1500
51/51 - 1s - loss: 0.7530 - categorical_accuracy: 0.7709 - val_loss: 0.7646 - val_categorical_accuracy: 0.7735 - 583ms/epoch - 11ms/step
Epoch 23/1500
51/51 - 1s - loss: 0.7440 - categorical_accuracy: 0.7713 - val_loss: 0.7528 - val_categorical_accuracy: 0.7739 - 541ms/epoch - 11ms/step
Epoch 24/1500
51/51 - 1s - loss: 0.7446 - categorical_accuracy: 0.7720 - val_loss: 0.7654 - val_categorical_accuracy: 0.7747 - 550ms/epoch - 11ms/step
Epoch 25/1500
51/51 - 1s - loss: 0.7464 - categorical_accuracy: 0.7722 - val_loss: 0.7537 - val_categorical_accuracy: 0.7734 - 543ms/epoch - 11ms/step
Epoch 26/1500
51/51 - 1s - loss: 0.7433 - categorical_accuracy: 0.7724 - val_loss: 0.7420 - val_categorical_accuracy: 0.7736 - 512ms/epoch - 10ms/step
Epoch 27/1500
51/51 - 1s - loss: 0.7306 - categorical_accuracy: 0.7727 - val_loss: 0.7439 - val_categorical_accuracy: 0.7738 - 544ms/epoch - 11ms/step
Epoch 28/1500
51/51 - 0s - loss: 0.7306 - categorical_accuracy: 0.7728 - val_loss: 0.7843 - val_categorical_accuracy: 0.7735 - 490ms/epoch - 10ms/step
Epoch 29/1500
51/51 - 1s - loss: 0.7253 - categorical_accuracy: 0.7744 - val_loss: 0.7432 - val_categorical_accuracy: 0.7760 - 556ms/epoch - 11ms/step
Epoch 30/1500
51/51 - 1s - loss: 0.7300 - categorical_accuracy: 0.7726 - val_loss: 0.7399 - val_categorical_accuracy: 0.7740 - 503ms/epoch - 10ms/step
Epoch 31/1500
51/51 - 1s - loss: 0.7194 - categorical_accuracy: 0.7731 - val_loss: 0.7530 - val_categorical_accuracy: 0.7740 - 600ms/epoch - 12ms/step
Epoch 32/1500
51/51 - 1s - loss: 0.7159 - categorical_accuracy: 0.7749 - val_loss: 0.7293 - val_categorical_accuracy: 0.7765 - 546ms/epoch - 11ms/step
Epoch 33/1500
51/51 - 1s - loss: 0.7159 - categorical_accuracy: 0.7749 - val_loss: 0.7462 - val_categorical_accuracy: 0.7703 - 542ms/epoch - 11ms/step
Epoch 34/1500
51/51 - 1s - loss: 0.7133 - categorical_accuracy: 0.7746 - val_loss: 0.8192 - val_categorical_accuracy: 0.7690 - 528ms/epoch - 10ms/step
Epoch 35/1500
51/51 - 1s - loss: 0.7081 - categorical_accuracy: 0.7755 - val_loss: 0.7314 - val_categorical_accuracy: 0.7771 - 540ms/epoch - 11ms/step
Epoch 36/1500
51/51 - 1s - loss: 0.7074 - categorical_accuracy: 0.7754 - val_loss: 0.7365 - val_categorical_accuracy: 0.7767 - 661ms/epoch - 13ms/step
Epoch 37/1500
51/51 - 1s - loss: 0.7020 - categorical_accuracy: 0.7767 - val_loss: 0.7147 - val_categorical_accuracy: 0.7784 - 625ms/epoch - 12ms/step
Epoch 38/1500
51/51 - 1s - loss: 0.6963 - categorical_accuracy: 0.7769 - val_loss: 0.7301 - val_categorical_accuracy: 0.7749 - 619ms/epoch - 12ms/step
Epoch 39/1500
51/51 - 1s - loss: 0.6938 - categorical_accuracy: 0.7777 - val_loss: 0.7716 - val_categorical_accuracy: 0.7409 - 520ms/epoch - 10ms/step
Epoch 40/1500
51/51 - 1s - loss: 0.6964 - categorical_accuracy: 0.7785 - val_loss: 0.7305 - val_categorical_accuracy: 0.7782 - 585ms/epoch - 11ms/step
Epoch 41/1500
51/51 - 1s - loss: 0.6866 - categorical_accuracy: 0.7782 - val_loss: 0.7450 - val_categorical_accuracy: 0.7765 - 602ms/epoch - 12ms/step
Epoch 42/1500
51/51 - 1s - loss: 0.6851 - categorical_accuracy: 0.7784 - val_loss: 0.7352 - val_categorical_accuracy: 0.7730 - 566ms/epoch - 11ms/step
Epoch 43/1500
51/51 - 1s - loss: 0.6812 - categorical_accuracy: 0.7794 - val_loss: 0.7238 - val_categorical_accuracy: 0.7792 - 585ms/epoch - 11ms/step
Epoch 44/1500
51/51 - 1s - loss: 0.6740 - categorical_accuracy: 0.7804 - val_loss: 0.7003 - val_categorical_accuracy: 0.7796 - 550ms/epoch - 11ms/step
Epoch 45/1500
51/51 - 1s - loss: 0.6664 - categorical_accuracy: 0.7840 - val_loss: 0.7224 - val_categorical_accuracy: 0.7763 - 566ms/epoch - 11ms/step
Epoch 46/1500
51/51 - 1s - loss: 0.6724 - categorical_accuracy: 0.7822 - val_loss: 0.6936 - val_categorical_accuracy: 0.7791 - 578ms/epoch - 11ms/step
Epoch 47/1500
51/51 - 1s - loss: 0.6670 - categorical_accuracy: 0.7840 - val_loss: 0.6992 - val_categorical_accuracy: 0.7797 - 576ms/epoch - 11ms/step
Epoch 48/1500
51/51 - 1s - loss: 0.6611 - categorical_accuracy: 0.7818 - val_loss: 0.7540 - val_categorical_accuracy: 0.7611 - 586ms/epoch - 11ms/step
Epoch 49/1500
51/51 - 1s - loss: 0.6663 - categorical_accuracy: 0.7829 - val_loss: 0.7285 - val_categorical_accuracy: 0.7791 - 554ms/epoch - 11ms/step
Epoch 50/1500
51/51 - 1s - loss: 0.6539 - categorical_accuracy: 0.7840 - val_loss: 0.7221 - val_categorical_accuracy: 0.7777 - 586ms/epoch - 11ms/step
Epoch 51/1500
51/51 - 1s - loss: 0.6493 - categorical_accuracy: 0.7849 - val_loss: 0.7262 - val_categorical_accuracy: 0.7608 - 569ms/epoch - 11ms/step
Epoch 52/1500
51/51 - 1s - loss: 0.6536 - categorical_accuracy: 0.7863 - val_loss: 0.7156 - val_categorical_accuracy: 0.7770 - 586ms/epoch - 11ms/step
Epoch 53/1500
51/51 - 1s - loss: 0.6430 - categorical_accuracy: 0.7884 - val_loss: 0.7438 - val_categorical_accuracy: 0.7642 - 611ms/epoch - 12ms/step
Epoch 54/1500
51/51 - 1s - loss: 0.6486 - categorical_accuracy: 0.7850 - val_loss: 0.6743 - val_categorical_accuracy: 0.7848 - 564ms/epoch - 11ms/step
Epoch 55/1500
51/51 - 1s - loss: 0.6404 - categorical_accuracy: 0.7866 - val_loss: 0.6902 - val_categorical_accuracy: 0.7793 - 584ms/epoch - 11ms/step
Epoch 56/1500
51/51 - 0s - loss: 0.6366 - categorical_accuracy: 0.7901 - val_loss: 0.7601 - val_categorical_accuracy: 0.7670 - 491ms/epoch - 10ms/step
Epoch 57/1500
51/51 - 1s - loss: 0.6343 - categorical_accuracy: 0.7900 - val_loss: 0.6859 - val_categorical_accuracy: 0.7769 - 584ms/epoch - 11ms/step
Epoch 58/1500
51/51 - 1s - loss: 0.6345 - categorical_accuracy: 0.7905 - val_loss: 0.6925 - val_categorical_accuracy: 0.7818 - 536ms/epoch - 11ms/step
Epoch 59/1500
51/51 - 1s - loss: 0.6263 - categorical_accuracy: 0.7933 - val_loss: 0.7173 - val_categorical_accuracy: 0.7829 - 522ms/epoch - 10ms/step
Epoch 60/1500
51/51 - 1s - loss: 0.6170 - categorical_accuracy: 0.7955 - val_loss: 0.6735 - val_categorical_accuracy: 0.7850 - 504ms/epoch - 10ms/step
Epoch 61/1500
51/51 - 1s - loss: 0.6240 - categorical_accuracy: 0.7930 - val_loss: 0.6753 - val_categorical_accuracy: 0.7822 - 525ms/epoch - 10ms/step
Epoch 62/1500
51/51 - 0s - loss: 0.6287 - categorical_accuracy: 0.7921 - val_loss: 0.6713 - val_categorical_accuracy: 0.7857 - 494ms/epoch - 10ms/step
Epoch 63/1500
51/51 - 1s - loss: 0.6177 - categorical_accuracy: 0.7939 - val_loss: 0.7111 - val_categorical_accuracy: 0.7707 - 515ms/epoch - 10ms/step
Epoch 64/1500
51/51 - 1s - loss: 0.6092 - categorical_accuracy: 0.7967 - val_loss: 0.6830 - val_categorical_accuracy: 0.7839 - 519ms/epoch - 10ms/step
Epoch 65/1500
51/51 - 1s - loss: 0.6101 - categorical_accuracy: 0.7973 - val_loss: 0.7141 - val_categorical_accuracy: 0.7589 - 520ms/epoch - 10ms/step
Epoch 66/1500
51/51 - 1s - loss: 0.6101 - categorical_accuracy: 0.7971 - val_loss: 0.6839 - val_categorical_accuracy: 0.7707 - 519ms/epoch - 10ms/step
Epoch 67/1500
51/51 - 1s - loss: 0.6099 - categorical_accuracy: 0.7959 - val_loss: 0.6715 - val_categorical_accuracy: 0.7885 - 525ms/epoch - 10ms/step
Epoch 68/1500
51/51 - 1s - loss: 0.5978 - categorical_accuracy: 0.7990 - val_loss: 0.7327 - val_categorical_accuracy: 0.7618 - 514ms/epoch - 10ms/step
Epoch 69/1500
51/51 - 1s - loss: 0.6023 - categorical_accuracy: 0.7993 - val_loss: 0.6642 - val_categorical_accuracy: 0.7841 - 544ms/epoch - 11ms/step
Epoch 70/1500
51/51 - 1s - loss: 0.5980 - categorical_accuracy: 0.7988 - val_loss: 0.6896 - val_categorical_accuracy: 0.7865 - 545ms/epoch - 11ms/step
Epoch 71/1500
51/51 - 0s - loss: 0.5873 - categorical_accuracy: 0.8012 - val_loss: 0.8486 - val_categorical_accuracy: 0.7778 - 490ms/epoch - 10ms/step
Epoch 72/1500
51/51 - 1s - loss: 0.5900 - categorical_accuracy: 0.8035 - val_loss: 0.7363 - val_categorical_accuracy: 0.7397 - 553ms/epoch - 11ms/step
Epoch 73/1500
51/51 - 0s - loss: 0.5779 - categorical_accuracy: 0.8055 - val_loss: 0.7161 - val_categorical_accuracy: 0.7860 - 489ms/epoch - 10ms/step
Epoch 74/1500
51/51 - 1s - loss: 0.5820 - categorical_accuracy: 0.8047 - val_loss: 0.7263 - val_categorical_accuracy: 0.7501 - 560ms/epoch - 11ms/step
Epoch 75/1500
51/51 - 1s - loss: 0.5857 - categorical_accuracy: 0.8045 - val_loss: 0.6858 - val_categorical_accuracy: 0.7882 - 510ms/epoch - 10ms/step
Epoch 76/1500
51/51 - 1s - loss: 0.5828 - categorical_accuracy: 0.8043 - val_loss: 0.6871 - val_categorical_accuracy: 0.7842 - 561ms/epoch - 11ms/step
Epoch 77/1500
51/51 - 0s - loss: 0.5705 - categorical_accuracy: 0.8069 - val_loss: 0.6848 - val_categorical_accuracy: 0.7757 - 497ms/epoch - 10ms/step
Epoch 78/1500
51/51 - 1s - loss: 0.5599 - categorical_accuracy: 0.8109 - val_loss: 0.7440 - val_categorical_accuracy: 0.7724 - 520ms/epoch - 10ms/step
Epoch 79/1500
51/51 - 1s - loss: 0.5663 - categorical_accuracy: 0.8075 - val_loss: 0.7892 - val_categorical_accuracy: 0.7126 - 507ms/epoch - 10ms/step
Epoch 80/1500
51/51 - 1s - loss: 0.5606 - categorical_accuracy: 0.8106 - val_loss: 0.6590 - val_categorical_accuracy: 0.7863 - 523ms/epoch - 10ms/step
Epoch 81/1500
51/51 - 1s - loss: 0.5628 - categorical_accuracy: 0.8078 - val_loss: 0.7490 - val_categorical_accuracy: 0.7770 - 553ms/epoch - 11ms/step
Epoch 82/1500
51/51 - 1s - loss: 0.5527 - categorical_accuracy: 0.8119 - val_loss: 0.7569 - val_categorical_accuracy: 0.7774 - 558ms/epoch - 11ms/step
Epoch 83/1500
51/51 - 1s - loss: 0.5476 - categorical_accuracy: 0.8135 - val_loss: 0.6857 - val_categorical_accuracy: 0.7879 - 519ms/epoch - 10ms/step
Epoch 84/1500
51/51 - 1s - loss: 0.5457 - categorical_accuracy: 0.8161 - val_loss: 0.7068 - val_categorical_accuracy: 0.7602 - 508ms/epoch - 10ms/step
Epoch 85/1500
51/51 - 1s - loss: 0.5513 - categorical_accuracy: 0.8124 - val_loss: 0.6562 - val_categorical_accuracy: 0.7929 - 540ms/epoch - 11ms/step
Epoch 86/1500
51/51 - 1s - loss: 0.5464 - categorical_accuracy: 0.8132 - val_loss: 0.6702 - val_categorical_accuracy: 0.7875 - 508ms/epoch - 10ms/step
Epoch 87/1500
51/51 - 1s - loss: 0.5459 - categorical_accuracy: 0.8162 - val_loss: 0.6856 - val_categorical_accuracy: 0.7708 - 518ms/epoch - 10ms/step
Epoch 88/1500
51/51 - 1s - loss: 0.5420 - categorical_accuracy: 0.8154 - val_loss: 0.6796 - val_categorical_accuracy: 0.7765 - 507ms/epoch - 10ms/step
Epoch 89/1500
51/51 - 1s - loss: 0.5355 - categorical_accuracy: 0.8190 - val_loss: 0.6811 - val_categorical_accuracy: 0.7883 - 532ms/epoch - 10ms/step
Epoch 90/1500
51/51 - 1s - loss: 0.5352 - categorical_accuracy: 0.8175 - val_loss: 0.7365 - val_categorical_accuracy: 0.7896 - 507ms/epoch - 10ms/step
Epoch 91/1500
51/51 - 1s - loss: 0.5360 - categorical_accuracy: 0.8185 - val_loss: 0.6879 - val_categorical_accuracy: 0.7712 - 592ms/epoch - 12ms/step
Epoch 92/1500
51/51 - 1s - loss: 0.5388 - categorical_accuracy: 0.8177 - val_loss: 0.6511 - val_categorical_accuracy: 0.7945 - 506ms/epoch - 10ms/step
Epoch 93/1500
51/51 - 1s - loss: 0.5209 - categorical_accuracy: 0.8218 - val_loss: 0.6787 - val_categorical_accuracy: 0.7897 - 580ms/epoch - 11ms/step
Epoch 94/1500
51/51 - 1s - loss: 0.5209 - categorical_accuracy: 0.8223 - val_loss: 0.6918 - val_categorical_accuracy: 0.7696 - 505ms/epoch - 10ms/step
Epoch 95/1500
51/51 - 1s - loss: 0.5225 - categorical_accuracy: 0.8191 - val_loss: 0.6686 - val_categorical_accuracy: 0.7908 - 521ms/epoch - 10ms/step
Epoch 96/1500
51/51 - 1s - loss: 0.5172 - categorical_accuracy: 0.8226 - val_loss: 0.6937 - val_categorical_accuracy: 0.7752 - 538ms/epoch - 11ms/step
Epoch 97/1500
51/51 - 1s - loss: 0.5232 - categorical_accuracy: 0.8214 - val_loss: 0.9113 - val_categorical_accuracy: 0.6638 - 554ms/epoch - 11ms/step
Epoch 98/1500
51/51 - 1s - loss: 0.5194 - categorical_accuracy: 0.8230 - val_loss: 0.6540 - val_categorical_accuracy: 0.7954 - 566ms/epoch - 11ms/step
Epoch 99/1500
51/51 - 1s - loss: 0.5132 - categorical_accuracy: 0.8220 - val_loss: 0.6850 - val_categorical_accuracy: 0.7841 - 522ms/epoch - 10ms/step
Epoch 100/1500
51/51 - 1s - loss: 0.5163 - categorical_accuracy: 0.8226 - val_loss: 0.6916 - val_categorical_accuracy: 0.7715 - 557ms/epoch - 11ms/step
Epoch 101/1500
51/51 - 1s - loss: 0.4886 - categorical_accuracy: 0.8319 - val_loss: 0.6922 - val_categorical_accuracy: 0.7743 - 530ms/epoch - 10ms/step
Epoch 102/1500
51/51 - 1s - loss: 0.4984 - categorical_accuracy: 0.8288 - val_loss: 0.7227 - val_categorical_accuracy: 0.7571 - 549ms/epoch - 11ms/step
Epoch 103/1500
51/51 - 1s - loss: 0.5077 - categorical_accuracy: 0.8274 - val_loss: 0.7038 - val_categorical_accuracy: 0.7627 - 508ms/epoch - 10ms/step
Epoch 104/1500
51/51 - 1s - loss: 0.4899 - categorical_accuracy: 0.8323 - val_loss: 0.6910 - val_categorical_accuracy: 0.7676 - 583ms/epoch - 11ms/step
Epoch 105/1500
51/51 - 1s - loss: 0.5024 - categorical_accuracy: 0.8293 - val_loss: 0.7745 - val_categorical_accuracy: 0.7879 - 533ms/epoch - 10ms/step
Epoch 106/1500
51/51 - 1s - loss: 0.4940 - categorical_accuracy: 0.8291 - val_loss: 0.6953 - val_categorical_accuracy: 0.7921 - 600ms/epoch - 12ms/step
Epoch 107/1500
51/51 - 1s - loss: 0.4985 - categorical_accuracy: 0.8267 - val_loss: 0.9059 - val_categorical_accuracy: 0.6924 - 558ms/epoch - 11ms/step
Epoch 108/1500
51/51 - 1s - loss: 0.4967 - categorical_accuracy: 0.8301 - val_loss: 0.7042 - val_categorical_accuracy: 0.7601 - 544ms/epoch - 11ms/step
Epoch 109/1500
51/51 - 1s - loss: 0.4817 - categorical_accuracy: 0.8327 - val_loss: 0.6513 - val_categorical_accuracy: 0.7984 - 562ms/epoch - 11ms/step
Epoch 110/1500
51/51 - 1s - loss: 0.4870 - categorical_accuracy: 0.8307 - val_loss: 0.6509 - val_categorical_accuracy: 0.7961 - 530ms/epoch - 10ms/step
Epoch 111/1500
51/51 - 1s - loss: 0.4781 - categorical_accuracy: 0.8325 - val_loss: 0.6763 - val_categorical_accuracy: 0.7915 - 616ms/epoch - 12ms/step
Epoch 112/1500
51/51 - 1s - loss: 0.4849 - categorical_accuracy: 0.8337 - val_loss: 0.6828 - val_categorical_accuracy: 0.7769 - 515ms/epoch - 10ms/step
Epoch 113/1500
51/51 - 1s - loss: 0.4795 - categorical_accuracy: 0.8376 - val_loss: 0.6665 - val_categorical_accuracy: 0.8009 - 562ms/epoch - 11ms/step
Epoch 114/1500
51/51 - 1s - loss: 0.4718 - categorical_accuracy: 0.8382 - val_loss: 0.6506 - val_categorical_accuracy: 0.7902 - 538ms/epoch - 11ms/step
Epoch 115/1500
51/51 - 1s - loss: 0.4611 - categorical_accuracy: 0.8421 - val_loss: 0.6615 - val_categorical_accuracy: 0.7878 - 564ms/epoch - 11ms/step
Epoch 116/1500
51/51 - 1s - loss: 0.4731 - categorical_accuracy: 0.8390 - val_loss: 0.6544 - val_categorical_accuracy: 0.7923 - 536ms/epoch - 11ms/step
Epoch 117/1500
51/51 - 1s - loss: 0.4705 - categorical_accuracy: 0.8361 - val_loss: 0.7410 - val_categorical_accuracy: 0.7921 - 550ms/epoch - 11ms/step
Epoch 118/1500
51/51 - 1s - loss: 0.4575 - categorical_accuracy: 0.8435 - val_loss: 0.6699 - val_categorical_accuracy: 0.7971 - 570ms/epoch - 11ms/step
Epoch 119/1500
51/51 - 1s - loss: 0.4632 - categorical_accuracy: 0.8411 - val_loss: 0.6656 - val_categorical_accuracy: 0.7839 - 509ms/epoch - 10ms/step
Epoch 120/1500
51/51 - 1s - loss: 0.4633 - categorical_accuracy: 0.8420 - val_loss: 0.6698 - val_categorical_accuracy: 0.7855 - 530ms/epoch - 10ms/step
Epoch 121/1500
51/51 - 1s - loss: 0.4615 - categorical_accuracy: 0.8403 - val_loss: 0.6930 - val_categorical_accuracy: 0.7996 - 525ms/epoch - 10ms/step
Epoch 122/1500
51/51 - 1s - loss: 0.4537 - categorical_accuracy: 0.8414 - val_loss: 0.6713 - val_categorical_accuracy: 0.7852 - 555ms/epoch - 11ms/step
Epoch 123/1500
51/51 - 0s - loss: 0.4461 - categorical_accuracy: 0.8461 - val_loss: 0.6771 - val_categorical_accuracy: 0.7928 - 491ms/epoch - 10ms/step
Epoch 124/1500
51/51 - 1s - loss: 0.4607 - categorical_accuracy: 0.8398 - val_loss: 0.6611 - val_categorical_accuracy: 0.7982 - 550ms/epoch - 11ms/step
Epoch 125/1500
51/51 - 0s - loss: 0.4464 - categorical_accuracy: 0.8441 - val_loss: 0.6562 - val_categorical_accuracy: 0.7943 - 499ms/epoch - 10ms/step
Epoch 126/1500
51/51 - 1s - loss: 0.4428 - categorical_accuracy: 0.8471 - val_loss: 0.6630 - val_categorical_accuracy: 0.7920 - 540ms/epoch - 11ms/step
Epoch 127/1500
51/51 - 1s - loss: 0.4446 - categorical_accuracy: 0.8479 - val_loss: 0.6971 - val_categorical_accuracy: 0.7827 - 518ms/epoch - 10ms/step
Epoch 128/1500
51/51 - 1s - loss: 0.4344 - categorical_accuracy: 0.8491 - val_loss: 0.6671 - val_categorical_accuracy: 0.7900 - 540ms/epoch - 11ms/step
Epoch 129/1500
51/51 - 1s - loss: 0.4517 - categorical_accuracy: 0.8432 - val_loss: 0.6714 - val_categorical_accuracy: 0.8005 - 502ms/epoch - 10ms/step
Epoch 130/1500
51/51 - 1s - loss: 0.4401 - categorical_accuracy: 0.8481 - val_loss: 0.6663 - val_categorical_accuracy: 0.7845 - 547ms/epoch - 11ms/step
Epoch 131/1500
51/51 - 1s - loss: 0.4307 - categorical_accuracy: 0.8505 - val_loss: 0.6704 - val_categorical_accuracy: 0.7985 - 527ms/epoch - 10ms/step
Epoch 132/1500
51/51 - 0s - loss: 0.4419 - categorical_accuracy: 0.8448 - val_loss: 0.6596 - val_categorical_accuracy: 0.7939 - 499ms/epoch - 10ms/step
Epoch 133/1500
51/51 - 1s - loss: 0.4260 - categorical_accuracy: 0.8539 - val_loss: 0.6722 - val_categorical_accuracy: 0.7847 - 528ms/epoch - 10ms/step
Epoch 134/1500
51/51 - 1s - loss: 0.4280 - categorical_accuracy: 0.8513 - val_loss: 0.7110 - val_categorical_accuracy: 0.7832 - 513ms/epoch - 10ms/step
Epoch 135/1500
51/51 - 1s - loss: 0.4308 - categorical_accuracy: 0.8500 - val_loss: 0.7557 - val_categorical_accuracy: 0.7852 - 535ms/epoch - 10ms/step
Epoch 136/1500
51/51 - 1s - loss: 0.4177 - categorical_accuracy: 0.8561 - val_loss: 0.7000 - val_categorical_accuracy: 0.7894 - 520ms/epoch - 10ms/step
Epoch 137/1500
51/51 - 1s - loss: 0.4216 - categorical_accuracy: 0.8553 - val_loss: 0.6775 - val_categorical_accuracy: 0.7887 - 523ms/epoch - 10ms/step
Epoch 138/1500
51/51 - 0s - loss: 0.4151 - categorical_accuracy: 0.8542 - val_loss: 0.6708 - val_categorical_accuracy: 0.7998 - 491ms/epoch - 10ms/step
Epoch 139/1500
51/51 - 1s - loss: 0.4296 - categorical_accuracy: 0.8512 - val_loss: 0.6665 - val_categorical_accuracy: 0.7969 - 548ms/epoch - 11ms/step
Epoch 140/1500
51/51 - 0s - loss: 0.4138 - categorical_accuracy: 0.8552 - val_loss: 0.6854 - val_categorical_accuracy: 0.8016 - 498ms/epoch - 10ms/step
Epoch 141/1500
51/51 - 1s - loss: 0.4079 - categorical_accuracy: 0.8598 - val_loss: 0.7318 - val_categorical_accuracy: 0.7601 - 527ms/epoch - 10ms/step
Epoch 142/1500
51/51 - 0s - loss: 0.4157 - categorical_accuracy: 0.8558 - val_loss: 0.6580 - val_categorical_accuracy: 0.8054 - 493ms/epoch - 10ms/step
Epoch 143/1500
51/51 - 1s - loss: 0.4037 - categorical_accuracy: 0.8585 - val_loss: 0.7510 - val_categorical_accuracy: 0.7538 - 536ms/epoch - 11ms/step
Epoch 144/1500
51/51 - 0s - loss: 0.4190 - categorical_accuracy: 0.8547 - val_loss: 0.7549 - val_categorical_accuracy: 0.7615 - 488ms/epoch - 10ms/step
Epoch 145/1500
51/51 - 1s - loss: 0.3989 - categorical_accuracy: 0.8632 - val_loss: 0.8872 - val_categorical_accuracy: 0.7558 - 588ms/epoch - 12ms/step
Epoch 146/1500
51/51 - 1s - loss: 0.4003 - categorical_accuracy: 0.8614 - val_loss: 0.7574 - val_categorical_accuracy: 0.7550 - 532ms/epoch - 10ms/step
Epoch 147/1500
51/51 - 1s - loss: 0.4076 - categorical_accuracy: 0.8573 - val_loss: 0.7031 - val_categorical_accuracy: 0.7857 - 572ms/epoch - 11ms/step
Epoch 148/1500
51/51 - 1s - loss: 0.3946 - categorical_accuracy: 0.8639 - val_loss: 0.8176 - val_categorical_accuracy: 0.7572 - 586ms/epoch - 11ms/step
Epoch 149/1500
51/51 - 1s - loss: 0.4113 - categorical_accuracy: 0.8575 - val_loss: 0.6848 - val_categorical_accuracy: 0.7867 - 542ms/epoch - 11ms/step
Epoch 150/1500
51/51 - 1s - loss: 0.3886 - categorical_accuracy: 0.8625 - val_loss: 0.7450 - val_categorical_accuracy: 0.7799 - 565ms/epoch - 11ms/step
Epoch 151/1500
51/51 - 1s - loss: 0.3875 - categorical_accuracy: 0.8652 - val_loss: 0.7117 - val_categorical_accuracy: 0.7995 - 803ms/epoch - 16ms/step
Epoch 152/1500
51/51 - 1s - loss: 0.3950 - categorical_accuracy: 0.8614 - val_loss: 0.6692 - val_categorical_accuracy: 0.7994 - 549ms/epoch - 11ms/step
Epoch 153/1500
51/51 - 1s - loss: 0.3905 - categorical_accuracy: 0.8653 - val_loss: 0.6843 - val_categorical_accuracy: 0.8045 - 533ms/epoch - 10ms/step
Epoch 154/1500
51/51 - 1s - loss: 0.3885 - categorical_accuracy: 0.8645 - val_loss: 0.7324 - val_categorical_accuracy: 0.7892 - 539ms/epoch - 11ms/step
Epoch 155/1500
51/51 - 1s - loss: 0.3861 - categorical_accuracy: 0.8660 - val_loss: 0.6822 - val_categorical_accuracy: 0.7964 - 558ms/epoch - 11ms/step
Epoch 156/1500
51/51 - 1s - loss: 0.3785 - categorical_accuracy: 0.8662 - val_loss: 0.7416 - val_categorical_accuracy: 0.7948 - 519ms/epoch - 10ms/step
Epoch 157/1500
51/51 - 1s - loss: 0.3806 - categorical_accuracy: 0.8660 - val_loss: 0.6817 - val_categorical_accuracy: 0.8014 - 566ms/epoch - 11ms/step
Epoch 158/1500
51/51 - 1s - loss: 0.3706 - categorical_accuracy: 0.8721 - val_loss: 0.8076 - val_categorical_accuracy: 0.7410 - 541ms/epoch - 11ms/step
Epoch 159/1500
51/51 - 1s - loss: 0.3793 - categorical_accuracy: 0.8663 - val_loss: 0.7279 - val_categorical_accuracy: 0.7924 - 539ms/epoch - 11ms/step
Epoch 160/1500
51/51 - 1s - loss: 0.3590 - categorical_accuracy: 0.8749 - val_loss: 0.7176 - val_categorical_accuracy: 0.8002 - 503ms/epoch - 10ms/step
Epoch 161/1500
51/51 - 1s - loss: 0.3757 - categorical_accuracy: 0.8689 - val_loss: 0.7832 - val_categorical_accuracy: 0.7726 - 572ms/epoch - 11ms/step
Epoch 162/1500
51/51 - 1s - loss: 0.3860 - categorical_accuracy: 0.8660 - val_loss: 0.7192 - val_categorical_accuracy: 0.7856 - 516ms/epoch - 10ms/step
Epoch 163/1500
51/51 - 1s - loss: 0.3833 - categorical_accuracy: 0.8672 - val_loss: 0.7006 - val_categorical_accuracy: 0.7877 - 547ms/epoch - 11ms/step
Epoch 164/1500
51/51 - 1s - loss: 0.3654 - categorical_accuracy: 0.8689 - val_loss: 0.8002 - val_categorical_accuracy: 0.7897 - 535ms/epoch - 10ms/step
Epoch 165/1500
51/51 - 1s - loss: 0.3684 - categorical_accuracy: 0.8697 - val_loss: 0.7387 - val_categorical_accuracy: 0.7756 - 534ms/epoch - 10ms/step
Epoch 166/1500
51/51 - 1s - loss: 0.3739 - categorical_accuracy: 0.8675 - val_loss: 0.7080 - val_categorical_accuracy: 0.8005 - 542ms/epoch - 11ms/step
Epoch 167/1500
51/51 - 1s - loss: 0.3495 - categorical_accuracy: 0.8772 - val_loss: 0.7648 - val_categorical_accuracy: 0.7861 - 546ms/epoch - 11ms/step
Epoch 168/1500
51/51 - 1s - loss: 0.3642 - categorical_accuracy: 0.8725 - val_loss: 0.7294 - val_categorical_accuracy: 0.7851 - 581ms/epoch - 11ms/step
Epoch 169/1500
51/51 - 1s - loss: 0.3644 - categorical_accuracy: 0.8732 - val_loss: 0.7349 - val_categorical_accuracy: 0.8003 - 564ms/epoch - 11ms/step
Epoch 170/1500
51/51 - 1s - loss: 0.3439 - categorical_accuracy: 0.8784 - val_loss: 0.7133 - val_categorical_accuracy: 0.8046 - 556ms/epoch - 11ms/step
Epoch 171/1500
51/51 - 1s - loss: 0.3652 - categorical_accuracy: 0.8699 - val_loss: 0.6917 - val_categorical_accuracy: 0.8060 - 511ms/epoch - 10ms/step
Epoch 172/1500
51/51 - 1s - loss: 0.3582 - categorical_accuracy: 0.8731 - val_loss: 0.7254 - val_categorical_accuracy: 0.7896 - 550ms/epoch - 11ms/step
Epoch 173/1500
51/51 - 1s - loss: 0.3602 - categorical_accuracy: 0.8722 - val_loss: 0.6976 - val_categorical_accuracy: 0.7903 - 536ms/epoch - 11ms/step
Epoch 174/1500
51/51 - 1s - loss: 0.3408 - categorical_accuracy: 0.8835 - val_loss: 0.7483 - val_categorical_accuracy: 0.7998 - 543ms/epoch - 11ms/step
Epoch 175/1500
51/51 - 1s - loss: 0.3526 - categorical_accuracy: 0.8745 - val_loss: 0.7163 - val_categorical_accuracy: 0.7964 - 542ms/epoch - 11ms/step
Epoch 176/1500
51/51 - 1s - loss: 0.3425 - categorical_accuracy: 0.8798 - val_loss: 0.7188 - val_categorical_accuracy: 0.8044 - 577ms/epoch - 11ms/step
Epoch 177/1500
51/51 - 1s - loss: 0.3414 - categorical_accuracy: 0.8804 - val_loss: 0.7943 - val_categorical_accuracy: 0.8008 - 535ms/epoch - 10ms/step
Epoch 178/1500
51/51 - 1s - loss: 0.3579 - categorical_accuracy: 0.8721 - val_loss: 0.7337 - val_categorical_accuracy: 0.7846 - 533ms/epoch - 10ms/step
Epoch 179/1500
51/51 - 1s - loss: 0.3391 - categorical_accuracy: 0.8823 - val_loss: 0.7187 - val_categorical_accuracy: 0.7942 - 569ms/epoch - 11ms/step
Epoch 180/1500
51/51 - 1s - loss: 0.3457 - categorical_accuracy: 0.8789 - val_loss: 0.7056 - val_categorical_accuracy: 0.7955 - 513ms/epoch - 10ms/step
Epoch 181/1500
51/51 - 1s - loss: 0.3389 - categorical_accuracy: 0.8819 - val_loss: 0.7116 - val_categorical_accuracy: 0.7913 - 568ms/epoch - 11ms/step
Epoch 182/1500
51/51 - 1s - loss: 0.3375 - categorical_accuracy: 0.8792 - val_loss: 0.8253 - val_categorical_accuracy: 0.7897 - 504ms/epoch - 10ms/step
Epoch 183/1500
51/51 - 1s - loss: 0.3367 - categorical_accuracy: 0.8826 - val_loss: 0.7339 - val_categorical_accuracy: 0.8027 - 542ms/epoch - 11ms/step
Epoch 184/1500
51/51 - 1s - loss: 0.3399 - categorical_accuracy: 0.8774 - val_loss: 0.7480 - val_categorical_accuracy: 0.7888 - 529ms/epoch - 10ms/step
Epoch 185/1500
51/51 - 1s - loss: 0.3198 - categorical_accuracy: 0.8866 - val_loss: 0.8198 - val_categorical_accuracy: 0.7864 - 556ms/epoch - 11ms/step
Epoch 186/1500
51/51 - 1s - loss: 0.3397 - categorical_accuracy: 0.8811 - val_loss: 0.7681 - val_categorical_accuracy: 0.7826 - 567ms/epoch - 11ms/step
Epoch 187/1500
51/51 - 1s - loss: 0.3307 - categorical_accuracy: 0.8816 - val_loss: 0.7465 - val_categorical_accuracy: 0.7997 - 536ms/epoch - 11ms/step
Epoch 188/1500
51/51 - 1s - loss: 0.3301 - categorical_accuracy: 0.8846 - val_loss: 0.7430 - val_categorical_accuracy: 0.8072 - 532ms/epoch - 10ms/step
Epoch 189/1500
51/51 - 1s - loss: 0.3223 - categorical_accuracy: 0.8874 - val_loss: 0.7748 - val_categorical_accuracy: 0.7870 - 510ms/epoch - 10ms/step
Epoch 190/1500
51/51 - 1s - loss: 0.3203 - categorical_accuracy: 0.8849 - val_loss: 0.8715 - val_categorical_accuracy: 0.7920 - 562ms/epoch - 11ms/step
Epoch 191/1500
51/51 - 1s - loss: 0.3364 - categorical_accuracy: 0.8787 - val_loss: 0.7623 - val_categorical_accuracy: 0.8012 - 510ms/epoch - 10ms/step
Epoch 192/1500
51/51 - 1s - loss: 0.3183 - categorical_accuracy: 0.8875 - val_loss: 0.8580 - val_categorical_accuracy: 0.7343 - 557ms/epoch - 11ms/step
Epoch 193/1500
51/51 - 1s - loss: 0.3175 - categorical_accuracy: 0.8882 - val_loss: 0.7276 - val_categorical_accuracy: 0.7933 - 522ms/epoch - 10ms/step
Epoch 194/1500
51/51 - 1s - loss: 0.3147 - categorical_accuracy: 0.8905 - val_loss: 0.8228 - val_categorical_accuracy: 0.8003 - 556ms/epoch - 11ms/step
Epoch 195/1500
51/51 - 1s - loss: 0.3146 - categorical_accuracy: 0.8875 - val_loss: 0.7328 - val_categorical_accuracy: 0.8049 - 517ms/epoch - 10ms/step
Epoch 196/1500
51/51 - 1s - loss: 0.3253 - categorical_accuracy: 0.8861 - val_loss: 0.7834 - val_categorical_accuracy: 0.7772 - 549ms/epoch - 11ms/step
Epoch 197/1500
51/51 - 1s - loss: 0.3126 - categorical_accuracy: 0.8893 - val_loss: 0.7412 - val_categorical_accuracy: 0.7972 - 508ms/epoch - 10ms/step
Epoch 198/1500
51/51 - 1s - loss: 0.3218 - categorical_accuracy: 0.8857 - val_loss: 0.7612 - val_categorical_accuracy: 0.8003 - 534ms/epoch - 10ms/step
Epoch 199/1500
51/51 - 1s - loss: 0.3240 - categorical_accuracy: 0.8853 - val_loss: 0.7931 - val_categorical_accuracy: 0.8050 - 520ms/epoch - 10ms/step
Epoch 200/1500
51/51 - 1s - loss: 0.3114 - categorical_accuracy: 0.8908 - val_loss: 0.7609 - val_categorical_accuracy: 0.7940 - 524ms/epoch - 10ms/step
Epoch 201/1500
51/51 - 1s - loss: 0.3158 - categorical_accuracy: 0.8864 - val_loss: 0.7351 - val_categorical_accuracy: 0.7978 - 534ms/epoch - 10ms/step
Epoch 202/1500
51/51 - 1s - loss: 0.3051 - categorical_accuracy: 0.8917 - val_loss: 0.7622 - val_categorical_accuracy: 0.8076 - 523ms/epoch - 10ms/step
Epoch 203/1500
51/51 - 1s - loss: 0.2998 - categorical_accuracy: 0.8948 - val_loss: 0.8249 - val_categorical_accuracy: 0.8014 - 560ms/epoch - 11ms/step
Epoch 204/1500
51/51 - 1s - loss: 0.3131 - categorical_accuracy: 0.8889 - val_loss: 0.8462 - val_categorical_accuracy: 0.8027 - 517ms/epoch - 10ms/step
Epoch 205/1500
51/51 - 1s - loss: 0.2953 - categorical_accuracy: 0.8966 - val_loss: 0.7801 - val_categorical_accuracy: 0.8071 - 539ms/epoch - 11ms/step
Epoch 206/1500
51/51 - 1s - loss: 0.2958 - categorical_accuracy: 0.8932 - val_loss: 0.7920 - val_categorical_accuracy: 0.8071 - 504ms/epoch - 10ms/step
Epoch 207/1500
51/51 - 1s - loss: 0.3001 - categorical_accuracy: 0.8938 - val_loss: 0.7849 - val_categorical_accuracy: 0.7909 - 548ms/epoch - 11ms/step
Epoch 208/1500
51/51 - 1s - loss: 0.2968 - categorical_accuracy: 0.8945 - val_loss: 0.7898 - val_categorical_accuracy: 0.7939 - 525ms/epoch - 10ms/step
Epoch 209/1500
51/51 - 1s - loss: 0.3067 - categorical_accuracy: 0.8893 - val_loss: 0.8885 - val_categorical_accuracy: 0.7543 - 556ms/epoch - 11ms/step
Epoch 210/1500
51/51 - 1s - loss: 0.2959 - categorical_accuracy: 0.8946 - val_loss: 0.8084 - val_categorical_accuracy: 0.7993 - 522ms/epoch - 10ms/step
Epoch 211/1500
51/51 - 1s - loss: 0.3144 - categorical_accuracy: 0.8866 - val_loss: 0.7649 - val_categorical_accuracy: 0.8014 - 563ms/epoch - 11ms/step
Epoch 212/1500
51/51 - 0s - loss: 0.3090 - categorical_accuracy: 0.8913 - val_loss: 0.7506 - val_categorical_accuracy: 0.8057 - 487ms/epoch - 10ms/step
Epoch 213/1500
51/51 - 1s - loss: 0.2767 - categorical_accuracy: 0.9017 - val_loss: 0.9840 - val_categorical_accuracy: 0.7949 - 534ms/epoch - 10ms/step
Epoch 214/1500
51/51 - 1s - loss: 0.2725 - categorical_accuracy: 0.9021 - val_loss: 0.8619 - val_categorical_accuracy: 0.8001 - 519ms/epoch - 10ms/step
Epoch 215/1500
51/51 - 1s - loss: 0.2981 - categorical_accuracy: 0.8929 - val_loss: 0.8085 - val_categorical_accuracy: 0.8098 - 531ms/epoch - 10ms/step
Epoch 216/1500
51/51 - 1s - loss: 0.2874 - categorical_accuracy: 0.8953 - val_loss: 0.7791 - val_categorical_accuracy: 0.7959 - 520ms/epoch - 10ms/step
Epoch 217/1500
51/51 - 1s - loss: 0.3031 - categorical_accuracy: 0.8931 - val_loss: 0.7708 - val_categorical_accuracy: 0.7981 - 524ms/epoch - 10ms/step
Epoch 218/1500
51/51 - 0s - loss: 0.2867 - categorical_accuracy: 0.8968 - val_loss: 0.8002 - val_categorical_accuracy: 0.7880 - 498ms/epoch - 10ms/step
Epoch 219/1500
51/51 - 1s - loss: 0.2820 - categorical_accuracy: 0.8990 - val_loss: 0.8742 - val_categorical_accuracy: 0.7979 - 547ms/epoch - 11ms/step
Epoch 220/1500
51/51 - 1s - loss: 0.2758 - categorical_accuracy: 0.9014 - val_loss: 0.8833 - val_categorical_accuracy: 0.7736 - 535ms/epoch - 10ms/step
Epoch 221/1500
51/51 - 1s - loss: 0.2872 - categorical_accuracy: 0.8958 - val_loss: 0.8471 - val_categorical_accuracy: 0.7785 - 523ms/epoch - 10ms/step
Epoch 222/1500
51/51 - 1s - loss: 0.2906 - categorical_accuracy: 0.8974 - val_loss: 0.7910 - val_categorical_accuracy: 0.8021 - 577ms/epoch - 11ms/step
Epoch 223/1500
51/51 - 1s - loss: 0.2692 - categorical_accuracy: 0.9035 - val_loss: 0.8546 - val_categorical_accuracy: 0.7942 - 523ms/epoch - 10ms/step
Epoch 224/1500
51/51 - 1s - loss: 0.2846 - categorical_accuracy: 0.8978 - val_loss: 0.8289 - val_categorical_accuracy: 0.7994 - 541ms/epoch - 11ms/step
Epoch 225/1500
51/51 - 1s - loss: 0.2690 - categorical_accuracy: 0.9035 - val_loss: 0.8162 - val_categorical_accuracy: 0.7870 - 522ms/epoch - 10ms/step
Epoch 226/1500
51/51 - 1s - loss: 0.2793 - categorical_accuracy: 0.8994 - val_loss: 0.8420 - val_categorical_accuracy: 0.7986 - 548ms/epoch - 11ms/step
Epoch 227/1500
51/51 - 1s - loss: 0.2907 - categorical_accuracy: 0.8959 - val_loss: 0.8296 - val_categorical_accuracy: 0.7864 - 508ms/epoch - 10ms/step
Epoch 228/1500
51/51 - 1s - loss: 0.2609 - categorical_accuracy: 0.9086 - val_loss: 0.7881 - val_categorical_accuracy: 0.8058 - 541ms/epoch - 11ms/step
Epoch 229/1500
51/51 - 1s - loss: 0.2788 - categorical_accuracy: 0.9010 - val_loss: 0.8214 - val_categorical_accuracy: 0.8036 - 533ms/epoch - 10ms/step
Epoch 230/1500
51/51 - 1s - loss: 0.2744 - categorical_accuracy: 0.9019 - val_loss: 0.8151 - val_categorical_accuracy: 0.8025 - 532ms/epoch - 10ms/step
Epoch 231/1500
51/51 - 1s - loss: 0.2663 - categorical_accuracy: 0.9040 - val_loss: 0.8836 - val_categorical_accuracy: 0.7712 - 547ms/epoch - 11ms/step
Epoch 232/1500
51/51 - 1s - loss: 0.2806 - categorical_accuracy: 0.9006 - val_loss: 0.8002 - val_categorical_accuracy: 0.8004 - 531ms/epoch - 10ms/step
Epoch 233/1500
51/51 - 1s - loss: 0.2756 - categorical_accuracy: 0.9019 - val_loss: 0.8242 - val_categorical_accuracy: 0.7915 - 534ms/epoch - 10ms/step
Epoch 234/1500
51/51 - 1s - loss: 0.2710 - categorical_accuracy: 0.8997 - val_loss: 0.8238 - val_categorical_accuracy: 0.7948 - 531ms/epoch - 10ms/step
Epoch 235/1500
51/51 - 1s - loss: 0.2852 - categorical_accuracy: 0.8973 - val_loss: 0.7995 - val_categorical_accuracy: 0.7925 - 555ms/epoch - 11ms/step
Epoch 236/1500
51/51 - 1s - loss: 0.2395 - categorical_accuracy: 0.9153 - val_loss: 0.8235 - val_categorical_accuracy: 0.8010 - 520ms/epoch - 10ms/step
Epoch 237/1500
51/51 - 1s - loss: 0.2419 - categorical_accuracy: 0.9129 - val_loss: 0.8900 - val_categorical_accuracy: 0.7957 - 567ms/epoch - 11ms/step
Epoch 238/1500
51/51 - 1s - loss: 0.2900 - categorical_accuracy: 0.8955 - val_loss: 1.1412 - val_categorical_accuracy: 0.6819 - 514ms/epoch - 10ms/step
Epoch 239/1500
51/51 - 1s - loss: 0.2849 - categorical_accuracy: 0.9018 - val_loss: 0.9849 - val_categorical_accuracy: 0.7581 - 550ms/epoch - 11ms/step
Epoch 240/1500
51/51 - 1s - loss: 0.2529 - categorical_accuracy: 0.9102 - val_loss: 0.8804 - val_categorical_accuracy: 0.8080 - 515ms/epoch - 10ms/step
Epoch 241/1500
51/51 - 1s - loss: 0.2733 - categorical_accuracy: 0.9009 - val_loss: 0.9991 - val_categorical_accuracy: 0.7711 - 563ms/epoch - 11ms/step
Epoch 242/1500
51/51 - 1s - loss: 0.2537 - categorical_accuracy: 0.9084 - val_loss: 0.8458 - val_categorical_accuracy: 0.7792 - 546ms/epoch - 11ms/step
Epoch 243/1500
51/51 - 1s - loss: 0.2662 - categorical_accuracy: 0.9047 - val_loss: 1.0190 - val_categorical_accuracy: 0.7859 - 558ms/epoch - 11ms/step
Epoch 244/1500
51/51 - 1s - loss: 0.2829 - categorical_accuracy: 0.9010 - val_loss: 0.7958 - val_categorical_accuracy: 0.7939 - 539ms/epoch - 11ms/step
Epoch 245/1500
51/51 - 1s - loss: 0.2445 - categorical_accuracy: 0.9111 - val_loss: 1.0208 - val_categorical_accuracy: 0.7941 - 510ms/epoch - 10ms/step
Epoch 246/1500
51/51 - 1s - loss: 0.2563 - categorical_accuracy: 0.9096 - val_loss: 0.9758 - val_categorical_accuracy: 0.7717 - 537ms/epoch - 11ms/step
Epoch 247/1500
51/51 - 0s - loss: 0.2490 - categorical_accuracy: 0.9121 - val_loss: 0.8916 - val_categorical_accuracy: 0.8031 - 490ms/epoch - 10ms/step
Epoch 248/1500
51/51 - 1s - loss: 0.2464 - categorical_accuracy: 0.9118 - val_loss: 0.8622 - val_categorical_accuracy: 0.8076 - 535ms/epoch - 10ms/step
Epoch 249/1500
51/51 - 1s - loss: 0.2677 - categorical_accuracy: 0.9071 - val_loss: 0.8317 - val_categorical_accuracy: 0.8080 - 508ms/epoch - 10ms/step
Epoch 250/1500
51/51 - 1s - loss: 0.2500 - categorical_accuracy: 0.9111 - val_loss: 0.8723 - val_categorical_accuracy: 0.7870 - 530ms/epoch - 10ms/step
Epoch 251/1500
51/51 - 0s - loss: 0.2333 - categorical_accuracy: 0.9168 - val_loss: 0.8548 - val_categorical_accuracy: 0.8056 - 488ms/epoch - 10ms/step
Epoch 252/1500
51/51 - 1s - loss: 0.2741 - categorical_accuracy: 0.9030 - val_loss: 0.8409 - val_categorical_accuracy: 0.7958 - 557ms/epoch - 11ms/step
Epoch 253/1500
51/51 - 0s - loss: 0.2396 - categorical_accuracy: 0.9138 - val_loss: 0.8551 - val_categorical_accuracy: 0.7984 - 490ms/epoch - 10ms/step
Epoch 254/1500
51/51 - 1s - loss: 0.2566 - categorical_accuracy: 0.9098 - val_loss: 0.9619 - val_categorical_accuracy: 0.7917 - 553ms/epoch - 11ms/step
Epoch 255/1500
51/51 - 0s - loss: 0.2471 - categorical_accuracy: 0.9097 - val_loss: 0.8959 - val_categorical_accuracy: 0.8039 - 495ms/epoch - 10ms/step
Epoch 256/1500
51/51 - 1s - loss: 0.2403 - categorical_accuracy: 0.9123 - val_loss: 0.9117 - val_categorical_accuracy: 0.7788 - 572ms/epoch - 11ms/step
Epoch 257/1500
51/51 - 1s - loss: 0.2487 - categorical_accuracy: 0.9105 - val_loss: 0.8931 - val_categorical_accuracy: 0.8022 - 533ms/epoch - 10ms/step
Epoch 258/1500
51/51 - 1s - loss: 0.2230 - categorical_accuracy: 0.9186 - val_loss: 0.9983 - val_categorical_accuracy: 0.7709 - 563ms/epoch - 11ms/step
Epoch 259/1500
51/51 - 1s - loss: 0.2583 - categorical_accuracy: 0.9074 - val_loss: 0.8780 - val_categorical_accuracy: 0.7868 - 577ms/epoch - 11ms/step
Epoch 260/1500
51/51 - 1s - loss: 0.2309 - categorical_accuracy: 0.9159 - val_loss: 0.9202 - val_categorical_accuracy: 0.7845 - 580ms/epoch - 11ms/step
Epoch 261/1500
51/51 - 1s - loss: 0.2224 - categorical_accuracy: 0.9212 - val_loss: 0.9333 - val_categorical_accuracy: 0.8051 - 585ms/epoch - 11ms/step
Epoch 262/1500
51/51 - 1s - loss: 0.2204 - categorical_accuracy: 0.9215 - val_loss: 0.9716 - val_categorical_accuracy: 0.7972 - 530ms/epoch - 10ms/step
Epoch 263/1500
51/51 - 1s - loss: 0.2558 - categorical_accuracy: 0.9080 - val_loss: 1.0786 - val_categorical_accuracy: 0.7293 - 576ms/epoch - 11ms/step
Epoch 264/1500
51/51 - 1s - loss: 0.2468 - categorical_accuracy: 0.9113 - val_loss: 0.9277 - val_categorical_accuracy: 0.7780 - 532ms/epoch - 10ms/step
Epoch 265/1500
51/51 - 1s - loss: 0.2418 - categorical_accuracy: 0.9141 - val_loss: 0.9584 - val_categorical_accuracy: 0.7569 - 587ms/epoch - 12ms/step
Epoch 266/1500
51/51 - 1s - loss: 0.2276 - categorical_accuracy: 0.9184 - val_loss: 0.9264 - val_categorical_accuracy: 0.7998 - 559ms/epoch - 11ms/step
Epoch 267/1500
51/51 - 1s - loss: 0.2413 - categorical_accuracy: 0.9140 - val_loss: 0.9400 - val_categorical_accuracy: 0.7907 - 569ms/epoch - 11ms/step
Epoch 268/1500
51/51 - 1s - loss: 0.2271 - categorical_accuracy: 0.9181 - val_loss: 1.0886 - val_categorical_accuracy: 0.7416 - 595ms/epoch - 12ms/step
Epoch 269/1500
51/51 - 1s - loss: 0.2855 - categorical_accuracy: 0.9007 - val_loss: 0.8755 - val_categorical_accuracy: 0.7943 - 543ms/epoch - 11ms/step
Epoch 270/1500
51/51 - 1s - loss: 0.2103 - categorical_accuracy: 0.9246 - val_loss: 0.9346 - val_categorical_accuracy: 0.8055 - 549ms/epoch - 11ms/step
Epoch 271/1500
51/51 - 1s - loss: 0.2263 - categorical_accuracy: 0.9180 - val_loss: 0.9174 - val_categorical_accuracy: 0.8046 - 558ms/epoch - 11ms/step
Epoch 272/1500
51/51 - 1s - loss: 0.2599 - categorical_accuracy: 0.9073 - val_loss: 0.8961 - val_categorical_accuracy: 0.7963 - 580ms/epoch - 11ms/step
Epoch 273/1500
51/51 - 1s - loss: 0.2156 - categorical_accuracy: 0.9223 - val_loss: 0.9424 - val_categorical_accuracy: 0.7612 - 542ms/epoch - 11ms/step
Epoch 274/1500
51/51 - 1s - loss: 0.2275 - categorical_accuracy: 0.9181 - val_loss: 0.9563 - val_categorical_accuracy: 0.8047 - 566ms/epoch - 11ms/step
Epoch 275/1500
51/51 - 1s - loss: 0.2145 - categorical_accuracy: 0.9240 - val_loss: 0.9373 - val_categorical_accuracy: 0.7936 - 555ms/epoch - 11ms/step
Epoch 276/1500
51/51 - 1s - loss: 0.2312 - categorical_accuracy: 0.9165 - val_loss: 0.9695 - val_categorical_accuracy: 0.7923 - 549ms/epoch - 11ms/step
Epoch 277/1500
51/51 - 1s - loss: 0.2494 - categorical_accuracy: 0.9130 - val_loss: 0.9125 - val_categorical_accuracy: 0.8002 - 622ms/epoch - 12ms/step
Epoch 278/1500
51/51 - 1s - loss: 0.1990 - categorical_accuracy: 0.9280 - val_loss: 0.9632 - val_categorical_accuracy: 0.7866 - 525ms/epoch - 10ms/step
Epoch 279/1500
51/51 - 1s - loss: 0.2915 - categorical_accuracy: 0.8981 - val_loss: 0.8480 - val_categorical_accuracy: 0.7996 - 588ms/epoch - 12ms/step
Epoch 280/1500
51/51 - 1s - loss: 0.2041 - categorical_accuracy: 0.9278 - val_loss: 0.9197 - val_categorical_accuracy: 0.7962 - 538ms/epoch - 11ms/step
Epoch 281/1500
51/51 - 1s - loss: 0.2085 - categorical_accuracy: 0.9258 - val_loss: 0.9438 - val_categorical_accuracy: 0.8085 - 540ms/epoch - 11ms/step
Epoch 282/1500
51/51 - 1s - loss: 0.2141 - categorical_accuracy: 0.9218 - val_loss: 0.9329 - val_categorical_accuracy: 0.8017 - 569ms/epoch - 11ms/step
Epoch 283/1500
51/51 - 1s - loss: 0.2014 - categorical_accuracy: 0.9270 - val_loss: 0.9667 - val_categorical_accuracy: 0.8009 - 575ms/epoch - 11ms/step
Epoch 284/1500
51/51 - 1s - loss: 0.2633 - categorical_accuracy: 0.9059 - val_loss: 0.9116 - val_categorical_accuracy: 0.8076 - 573ms/epoch - 11ms/step
Epoch 285/1500
51/51 - 1s - loss: 0.2104 - categorical_accuracy: 0.9239 - val_loss: 0.9924 - val_categorical_accuracy: 0.7815 - 524ms/epoch - 10ms/step
Epoch 286/1500
51/51 - 1s - loss: 0.2317 - categorical_accuracy: 0.9162 - val_loss: 1.0376 - val_categorical_accuracy: 0.8073 - 574ms/epoch - 11ms/step
Epoch 287/1500
51/51 - 1s - loss: 0.2070 - categorical_accuracy: 0.9262 - val_loss: 1.0003 - val_categorical_accuracy: 0.7859 - 525ms/epoch - 10ms/step
Epoch 288/1500
51/51 - 1s - loss: 0.2141 - categorical_accuracy: 0.9202 - val_loss: 1.0275 - val_categorical_accuracy: 0.7856 - 597ms/epoch - 12ms/step
Epoch 289/1500
51/51 - 1s - loss: 0.2171 - categorical_accuracy: 0.9224 - val_loss: 0.9967 - val_categorical_accuracy: 0.7818 - 540ms/epoch - 11ms/step
Epoch 290/1500
51/51 - 1s - loss: 0.2141 - categorical_accuracy: 0.9222 - val_loss: 1.1461 - val_categorical_accuracy: 0.7470 - 563ms/epoch - 11ms/step
Epoch 291/1500
51/51 - 1s - loss: 0.2153 - categorical_accuracy: 0.9225 - val_loss: 0.9861 - val_categorical_accuracy: 0.7962 - 566ms/epoch - 11ms/step
Epoch 292/1500
51/51 - 1s - loss: 0.2352 - categorical_accuracy: 0.9177 - val_loss: 0.9438 - val_categorical_accuracy: 0.7836 - 518ms/epoch - 10ms/step
Epoch 293/1500
51/51 - 1s - loss: 0.1949 - categorical_accuracy: 0.9296 - val_loss: 1.0318 - val_categorical_accuracy: 0.7997 - 588ms/epoch - 12ms/step
Epoch 294/1500
51/51 - 1s - loss: 0.2444 - categorical_accuracy: 0.9137 - val_loss: 0.9767 - val_categorical_accuracy: 0.7949 - 552ms/epoch - 11ms/step
Epoch 295/1500
51/51 - 1s - loss: 0.1875 - categorical_accuracy: 0.9326 - val_loss: 0.9802 - val_categorical_accuracy: 0.8054 - 619ms/epoch - 12ms/step
Epoch 296/1500
51/51 - 1s - loss: 0.2170 - categorical_accuracy: 0.9230 - val_loss: 0.9550 - val_categorical_accuracy: 0.7917 - 532ms/epoch - 10ms/step
Epoch 297/1500
51/51 - 1s - loss: 0.2056 - categorical_accuracy: 0.9275 - val_loss: 0.9924 - val_categorical_accuracy: 0.7727 - 560ms/epoch - 11ms/step
Epoch 298/1500
51/51 - 1s - loss: 0.1969 - categorical_accuracy: 0.9293 - val_loss: 1.0097 - val_categorical_accuracy: 0.7840 - 565ms/epoch - 11ms/step
Epoch 299/1500
51/51 - 1s - loss: 0.2174 - categorical_accuracy: 0.9238 - val_loss: 0.9679 - val_categorical_accuracy: 0.8064 - 555ms/epoch - 11ms/step
Epoch 300/1500
51/51 - 1s - loss: 0.1984 - categorical_accuracy: 0.9282 - val_loss: 1.0688 - val_categorical_accuracy: 0.8019 - 520ms/epoch - 10ms/step
Epoch 301/1500
51/51 - 1s - loss: 0.2034 - categorical_accuracy: 0.9255 - val_loss: 1.0019 - val_categorical_accuracy: 0.7943 - 515ms/epoch - 10ms/step
Epoch 302/1500
51/51 - 1s - loss: 0.1877 - categorical_accuracy: 0.9323 - val_loss: 1.0139 - val_categorical_accuracy: 0.8010 - 538ms/epoch - 11ms/step
Epoch 303/1500
51/51 - 0s - loss: 0.2515 - categorical_accuracy: 0.9132 - val_loss: 0.9389 - val_categorical_accuracy: 0.8053 - 491ms/epoch - 10ms/step
Epoch 304/1500
51/51 - 1s - loss: 0.2051 - categorical_accuracy: 0.9260 - val_loss: 1.0993 - val_categorical_accuracy: 0.7660 - 535ms/epoch - 10ms/step
Epoch 305/1500
51/51 - 1s - loss: 0.2174 - categorical_accuracy: 0.9211 - val_loss: 1.0985 - val_categorical_accuracy: 0.7980 - 503ms/epoch - 10ms/step
Epoch 306/1500
51/51 - 1s - loss: 0.1844 - categorical_accuracy: 0.9344 - val_loss: 1.0417 - val_categorical_accuracy: 0.7942 - 525ms/epoch - 10ms/step
Epoch 307/1500
51/51 - 1s - loss: 0.2254 - categorical_accuracy: 0.9215 - val_loss: 0.9666 - val_categorical_accuracy: 0.8043 - 500ms/epoch - 10ms/step
Epoch 308/1500
51/51 - 1s - loss: 0.2026 - categorical_accuracy: 0.9278 - val_loss: 1.0842 - val_categorical_accuracy: 0.7640 - 535ms/epoch - 10ms/step
Epoch 309/1500
51/51 - 0s - loss: 0.1811 - categorical_accuracy: 0.9345 - val_loss: 1.0475 - val_categorical_accuracy: 0.7836 - 483ms/epoch - 9ms/step
Epoch 310/1500
51/51 - 1s - loss: 0.1924 - categorical_accuracy: 0.9294 - val_loss: 1.0317 - val_categorical_accuracy: 0.8030 - 521ms/epoch - 10ms/step
Epoch 311/1500
51/51 - 0s - loss: 0.2216 - categorical_accuracy: 0.9204 - val_loss: 1.0235 - val_categorical_accuracy: 0.7711 - 500ms/epoch - 10ms/step
Epoch 312/1500
51/51 - 1s - loss: 0.1782 - categorical_accuracy: 0.9357 - val_loss: 1.0193 - val_categorical_accuracy: 0.8018 - 531ms/epoch - 10ms/step
Epoch 313/1500
51/51 - 1s - loss: 0.1880 - categorical_accuracy: 0.9331 - val_loss: 1.0917 - val_categorical_accuracy: 0.7713 - 510ms/epoch - 10ms/step
Epoch 314/1500
51/51 - 1s - loss: 0.1978 - categorical_accuracy: 0.9278 - val_loss: 1.0602 - val_categorical_accuracy: 0.7953 - 548ms/epoch - 11ms/step
Epoch 315/1500
51/51 - 0s - loss: 0.2155 - categorical_accuracy: 0.9230 - val_loss: 0.9890 - val_categorical_accuracy: 0.7964 - 491ms/epoch - 10ms/step
Epoch 316/1500
51/51 - 1s - loss: 0.1793 - categorical_accuracy: 0.9360 - val_loss: 1.0130 - val_categorical_accuracy: 0.8000 - 519ms/epoch - 10ms/step
Epoch 317/1500
51/51 - 1s - loss: 0.2742 - categorical_accuracy: 0.9098 - val_loss: 0.9066 - val_categorical_accuracy: 0.8025 - 534ms/epoch - 10ms/step
Epoch 318/1500
51/51 - 1s - loss: 0.1816 - categorical_accuracy: 0.9359 - val_loss: 1.0074 - val_categorical_accuracy: 0.8098 - 528ms/epoch - 10ms/step
Epoch 319/1500
51/51 - 1s - loss: 0.1730 - categorical_accuracy: 0.9381 - val_loss: 1.0682 - val_categorical_accuracy: 0.7907 - 541ms/epoch - 11ms/step
Epoch 320/1500
51/51 - 1s - loss: 0.2016 - categorical_accuracy: 0.9268 - val_loss: 1.0033 - val_categorical_accuracy: 0.8034 - 526ms/epoch - 10ms/step
Epoch 321/1500
51/51 - 1s - loss: 0.2328 - categorical_accuracy: 0.9208 - val_loss: 0.9805 - val_categorical_accuracy: 0.8019 - 539ms/epoch - 11ms/step
Epoch 322/1500
51/51 - 1s - loss: 0.1697 - categorical_accuracy: 0.9380 - val_loss: 1.0543 - val_categorical_accuracy: 0.7926 - 525ms/epoch - 10ms/step
Epoch 323/1500
51/51 - 1s - loss: 0.1849 - categorical_accuracy: 0.9328 - val_loss: 1.0349 - val_categorical_accuracy: 0.8032 - 553ms/epoch - 11ms/step
Epoch 324/1500
51/51 - 1s - loss: 0.1678 - categorical_accuracy: 0.9400 - val_loss: 1.1451 - val_categorical_accuracy: 0.7737 - 508ms/epoch - 10ms/step
Epoch 325/1500
51/51 - 1s - loss: 0.2289 - categorical_accuracy: 0.9200 - val_loss: 1.1655 - val_categorical_accuracy: 0.7706 - 534ms/epoch - 10ms/step
Epoch 326/1500
51/51 - 0s - loss: 0.1861 - categorical_accuracy: 0.9329 - val_loss: 1.0805 - val_categorical_accuracy: 0.7974 - 494ms/epoch - 10ms/step
Epoch 327/1500
51/51 - 1s - loss: 0.2124 - categorical_accuracy: 0.9239 - val_loss: 1.0852 - val_categorical_accuracy: 0.7703 - 528ms/epoch - 10ms/step
Epoch 328/1500
51/51 - 0s - loss: 0.1818 - categorical_accuracy: 0.9341 - val_loss: 1.1107 - val_categorical_accuracy: 0.8079 - 486ms/epoch - 10ms/step
Epoch 329/1500
51/51 - 1s - loss: 0.2023 - categorical_accuracy: 0.9276 - val_loss: 1.0577 - val_categorical_accuracy: 0.8088 - 557ms/epoch - 11ms/step
Epoch 330/1500
51/51 - 0s - loss: 0.1941 - categorical_accuracy: 0.9304 - val_loss: 1.1257 - val_categorical_accuracy: 0.7874 - 492ms/epoch - 10ms/step
Epoch 331/1500
51/51 - 1s - loss: 0.1647 - categorical_accuracy: 0.9409 - val_loss: 1.0712 - val_categorical_accuracy: 0.7989 - 553ms/epoch - 11ms/step
Epoch 332/1500
51/51 - 1s - loss: 0.1679 - categorical_accuracy: 0.9392 - val_loss: 1.1269 - val_categorical_accuracy: 0.7898 - 500ms/epoch - 10ms/step
Epoch 333/1500
51/51 - 1s - loss: 0.1673 - categorical_accuracy: 0.9383 - val_loss: 1.3597 - val_categorical_accuracy: 0.7267 - 508ms/epoch - 10ms/step
Epoch 334/1500
51/51 - 0s - loss: 0.2439 - categorical_accuracy: 0.9162 - val_loss: 1.0290 - val_categorical_accuracy: 0.8010 - 499ms/epoch - 10ms/step
Epoch 335/1500
51/51 - 1s - loss: 0.1677 - categorical_accuracy: 0.9380 - val_loss: 1.1163 - val_categorical_accuracy: 0.7985 - 547ms/epoch - 11ms/step
Epoch 336/1500
51/51 - 0s - loss: 0.1667 - categorical_accuracy: 0.9403 - val_loss: 1.1193 - val_categorical_accuracy: 0.8069 - 491ms/epoch - 10ms/step
Epoch 337/1500
51/51 - 1s - loss: 0.2422 - categorical_accuracy: 0.9152 - val_loss: 1.0693 - val_categorical_accuracy: 0.7724 - 541ms/epoch - 11ms/step
Epoch 338/1500
51/51 - 0s - loss: 0.1815 - categorical_accuracy: 0.9328 - val_loss: 1.0691 - val_categorical_accuracy: 0.7828 - 499ms/epoch - 10ms/step
Epoch 339/1500
51/51 - 1s - loss: 0.1873 - categorical_accuracy: 0.9337 - val_loss: 1.1788 - val_categorical_accuracy: 0.7447 - 516ms/epoch - 10ms/step
Epoch 340/1500
51/51 - 1s - loss: 0.2070 - categorical_accuracy: 0.9274 - val_loss: 1.0573 - val_categorical_accuracy: 0.7913 - 516ms/epoch - 10ms/step
Epoch 341/1500
51/51 - 1s - loss: 0.1689 - categorical_accuracy: 0.9392 - val_loss: 1.0803 - val_categorical_accuracy: 0.8007 - 558ms/epoch - 11ms/step
Epoch 342/1500
51/51 - 1s - loss: 0.1579 - categorical_accuracy: 0.9425 - val_loss: 1.1415 - val_categorical_accuracy: 0.7980 - 547ms/epoch - 11ms/step
Epoch 343/1500
51/51 - 1s - loss: 0.1650 - categorical_accuracy: 0.9395 - val_loss: 1.1294 - val_categorical_accuracy: 0.8037 - 557ms/epoch - 11ms/step
Epoch 344/1500
51/51 - 1s - loss: 0.1654 - categorical_accuracy: 0.9399 - val_loss: 1.2205 - val_categorical_accuracy: 0.8072 - 559ms/epoch - 11ms/step
Epoch 345/1500
51/51 - 1s - loss: 0.1604 - categorical_accuracy: 0.9428 - val_loss: 1.1919 - val_categorical_accuracy: 0.7778 - 508ms/epoch - 10ms/step
Epoch 346/1500
51/51 - 1s - loss: 0.2218 - categorical_accuracy: 0.9217 - val_loss: 1.0832 - val_categorical_accuracy: 0.8003 - 569ms/epoch - 11ms/step
Epoch 347/1500
51/51 - 1s - loss: 0.1705 - categorical_accuracy: 0.9383 - val_loss: 1.1617 - val_categorical_accuracy: 0.7936 - 534ms/epoch - 10ms/step
Epoch 348/1500
51/51 - 1s - loss: 0.1820 - categorical_accuracy: 0.9322 - val_loss: 1.1113 - val_categorical_accuracy: 0.8007 - 575ms/epoch - 11ms/step
Epoch 349/1500
51/51 - 1s - loss: 0.2183 - categorical_accuracy: 0.9276 - val_loss: 0.9990 - val_categorical_accuracy: 0.7989 - 536ms/epoch - 11ms/step
Epoch 350/1500
51/51 - 1s - loss: 0.1613 - categorical_accuracy: 0.9416 - val_loss: 1.1114 - val_categorical_accuracy: 0.7996 - 566ms/epoch - 11ms/step
Epoch 351/1500
51/51 - 1s - loss: 0.1516 - categorical_accuracy: 0.9450 - val_loss: 1.1202 - val_categorical_accuracy: 0.8090 - 546ms/epoch - 11ms/step
Epoch 352/1500
51/51 - 1s - loss: 0.1973 - categorical_accuracy: 0.9273 - val_loss: 1.1182 - val_categorical_accuracy: 0.7851 - 538ms/epoch - 11ms/step
Epoch 353/1500
51/51 - 1s - loss: 0.1601 - categorical_accuracy: 0.9420 - val_loss: 1.2178 - val_categorical_accuracy: 0.7879 - 525ms/epoch - 10ms/step
Epoch 354/1500
51/51 - 1s - loss: 0.1874 - categorical_accuracy: 0.9339 - val_loss: 1.4155 - val_categorical_accuracy: 0.7097 - 506ms/epoch - 10ms/step
Epoch 355/1500
51/51 - 1s - loss: 0.1918 - categorical_accuracy: 0.9349 - val_loss: 1.1299 - val_categorical_accuracy: 0.7909 - 536ms/epoch - 11ms/step
Epoch 356/1500
51/51 - 1s - loss: 0.1545 - categorical_accuracy: 0.9435 - val_loss: 1.1353 - val_categorical_accuracy: 0.8071 - 507ms/epoch - 10ms/step
Epoch 357/1500
51/51 - 1s - loss: 0.1816 - categorical_accuracy: 0.9333 - val_loss: 1.2639 - val_categorical_accuracy: 0.7417 - 512ms/epoch - 10ms/step
Epoch 358/1500
51/51 - 0s - loss: 0.2016 - categorical_accuracy: 0.9297 - val_loss: 1.1297 - val_categorical_accuracy: 0.8086 - 498ms/epoch - 10ms/step
Epoch 359/1500
51/51 - 1s - loss: 0.1672 - categorical_accuracy: 0.9388 - val_loss: 1.1229 - val_categorical_accuracy: 0.8016 - 522ms/epoch - 10ms/step
Epoch 360/1500
51/51 - 0s - loss: 0.1504 - categorical_accuracy: 0.9464 - val_loss: 1.2317 - val_categorical_accuracy: 0.7995 - 493ms/epoch - 10ms/step
Epoch 361/1500
51/51 - 1s - loss: 0.1577 - categorical_accuracy: 0.9421 - val_loss: 1.1804 - val_categorical_accuracy: 0.7863 - 539ms/epoch - 11ms/step
Epoch 362/1500
51/51 - 0s - loss: 0.2374 - categorical_accuracy: 0.9230 - val_loss: 1.1228 - val_categorical_accuracy: 0.7576 - 487ms/epoch - 10ms/step
Epoch 363/1500
51/51 - 1s - loss: 0.1661 - categorical_accuracy: 0.9396 - val_loss: 1.1868 - val_categorical_accuracy: 0.7656 - 524ms/epoch - 10ms/step
Epoch 364/1500
51/51 - 0s - loss: 0.1559 - categorical_accuracy: 0.9429 - val_loss: 1.1442 - val_categorical_accuracy: 0.8010 - 484ms/epoch - 9ms/step
Epoch 365/1500
51/51 - 1s - loss: 0.1598 - categorical_accuracy: 0.9416 - val_loss: 1.2086 - val_categorical_accuracy: 0.8071 - 554ms/epoch - 11ms/step
Epoch 366/1500
51/51 - 0s - loss: 0.1522 - categorical_accuracy: 0.9449 - val_loss: 1.1700 - val_categorical_accuracy: 0.8030 - 493ms/epoch - 10ms/step
Epoch 367/1500
51/51 - 1s - loss: 0.2222 - categorical_accuracy: 0.9223 - val_loss: 1.0879 - val_categorical_accuracy: 0.7925 - 547ms/epoch - 11ms/step
Epoch 368/1500
51/51 - 0s - loss: 0.1457 - categorical_accuracy: 0.9471 - val_loss: 1.2705 - val_categorical_accuracy: 0.8072 - 485ms/epoch - 10ms/step
Epoch 369/1500
51/51 - 1s - loss: 0.1504 - categorical_accuracy: 0.9453 - val_loss: 1.1599 - val_categorical_accuracy: 0.8034 - 526ms/epoch - 10ms/step
Epoch 370/1500
51/51 - 0s - loss: 0.1586 - categorical_accuracy: 0.9414 - val_loss: 1.2321 - val_categorical_accuracy: 0.8068 - 483ms/epoch - 9ms/step
Epoch 371/1500
51/51 - 1s - loss: 0.1794 - categorical_accuracy: 0.9353 - val_loss: 1.2274 - val_categorical_accuracy: 0.7994 - 576ms/epoch - 11ms/step
Epoch 372/1500
51/51 - 0s - loss: 0.1939 - categorical_accuracy: 0.9331 - val_loss: 1.1972 - val_categorical_accuracy: 0.7370 - 496ms/epoch - 10ms/step
Epoch 373/1500
51/51 - 1s - loss: 0.1698 - categorical_accuracy: 0.9390 - val_loss: 1.2202 - val_categorical_accuracy: 0.8014 - 524ms/epoch - 10ms/step
Epoch 374/1500
51/51 - 1s - loss: 0.1539 - categorical_accuracy: 0.9446 - val_loss: 1.2218 - val_categorical_accuracy: 0.8036 - 506ms/epoch - 10ms/step
Epoch 375/1500
51/51 - 1s - loss: 0.2600 - categorical_accuracy: 0.9158 - val_loss: 1.0284 - val_categorical_accuracy: 0.7972 - 511ms/epoch - 10ms/step
Epoch 376/1500
51/51 - 0s - loss: 0.1547 - categorical_accuracy: 0.9437 - val_loss: 1.1455 - val_categorical_accuracy: 0.8000 - 496ms/epoch - 10ms/step
Epoch 377/1500
51/51 - 1s - loss: 0.1405 - categorical_accuracy: 0.9493 - val_loss: 1.1838 - val_categorical_accuracy: 0.8037 - 520ms/epoch - 10ms/step
Epoch 378/1500
51/51 - 1s - loss: 0.1399 - categorical_accuracy: 0.9490 - val_loss: 1.2040 - val_categorical_accuracy: 0.7932 - 526ms/epoch - 10ms/step
Epoch 379/1500
51/51 - 1s - loss: 0.1433 - categorical_accuracy: 0.9485 - val_loss: 1.2967 - val_categorical_accuracy: 0.8087 - 522ms/epoch - 10ms/step
Epoch 380/1500
51/51 - 1s - loss: 0.1465 - categorical_accuracy: 0.9476 - val_loss: 1.1914 - val_categorical_accuracy: 0.7983 - 512ms/epoch - 10ms/step
Epoch 381/1500
51/51 - 1s - loss: 0.2095 - categorical_accuracy: 0.9286 - val_loss: 1.1857 - val_categorical_accuracy: 0.7923 - 502ms/epoch - 10ms/step
Epoch 382/1500
51/51 - 1s - loss: 0.1473 - categorical_accuracy: 0.9461 - val_loss: 1.2175 - val_categorical_accuracy: 0.8057 - 511ms/epoch - 10ms/step
Epoch 383/1500
51/51 - 1s - loss: 0.1587 - categorical_accuracy: 0.9421 - val_loss: 1.1816 - val_categorical_accuracy: 0.8011 - 505ms/epoch - 10ms/step
Epoch 384/1500
51/51 - 1s - loss: 0.1403 - categorical_accuracy: 0.9481 - val_loss: 1.2271 - val_categorical_accuracy: 0.8109 - 523ms/epoch - 10ms/step
Epoch 385/1500
51/51 - 1s - loss: 0.2351 - categorical_accuracy: 0.9213 - val_loss: 1.0612 - val_categorical_accuracy: 0.7887 - 509ms/epoch - 10ms/step
Epoch 386/1500
51/51 - 1s - loss: 0.1461 - categorical_accuracy: 0.9474 - val_loss: 1.1882 - val_categorical_accuracy: 0.8032 - 515ms/epoch - 10ms/step
Epoch 387/1500
51/51 - 0s - loss: 0.1419 - categorical_accuracy: 0.9482 - val_loss: 1.2644 - val_categorical_accuracy: 0.8030 - 493ms/epoch - 10ms/step
Epoch 388/1500
51/51 - 1s - loss: 0.2275 - categorical_accuracy: 0.9219 - val_loss: 1.1138 - val_categorical_accuracy: 0.7922 - 522ms/epoch - 10ms/step
Epoch 389/1500
51/51 - 1s - loss: 0.1527 - categorical_accuracy: 0.9440 - val_loss: 1.1837 - val_categorical_accuracy: 0.7978 - 509ms/epoch - 10ms/step
Epoch 390/1500
51/51 - 1s - loss: 0.1396 - categorical_accuracy: 0.9507 - val_loss: 1.2012 - val_categorical_accuracy: 0.7971 - 561ms/epoch - 11ms/step
Epoch 391/1500
51/51 - 1s - loss: 0.1423 - categorical_accuracy: 0.9482 - val_loss: 1.3181 - val_categorical_accuracy: 0.8002 - 508ms/epoch - 10ms/step
Epoch 392/1500
51/51 - 1s - loss: 0.2137 - categorical_accuracy: 0.9293 - val_loss: 1.1854 - val_categorical_accuracy: 0.8018 - 524ms/epoch - 10ms/step
Epoch 393/1500
51/51 - 0s - loss: 0.1335 - categorical_accuracy: 0.9516 - val_loss: 1.1979 - val_categorical_accuracy: 0.8010 - 475ms/epoch - 9ms/step
Epoch 394/1500
51/51 - 1s - loss: 0.1395 - categorical_accuracy: 0.9495 - val_loss: 1.2774 - val_categorical_accuracy: 0.7773 - 540ms/epoch - 11ms/step
Epoch 395/1500
51/51 - 0s - loss: 0.1451 - categorical_accuracy: 0.9476 - val_loss: 1.2487 - val_categorical_accuracy: 0.7990 - 491ms/epoch - 10ms/step
Epoch 396/1500
51/51 - 1s - loss: 0.1737 - categorical_accuracy: 0.9377 - val_loss: 1.2276 - val_categorical_accuracy: 0.8019 - 521ms/epoch - 10ms/step
Epoch 397/1500
51/51 - 0s - loss: 0.2062 - categorical_accuracy: 0.9295 - val_loss: 1.1528 - val_categorical_accuracy: 0.7987 - 495ms/epoch - 10ms/step
Epoch 398/1500
51/51 - 1s - loss: 0.1544 - categorical_accuracy: 0.9436 - val_loss: 1.1765 - val_categorical_accuracy: 0.7856 - 535ms/epoch - 10ms/step
Epoch 399/1500
51/51 - 0s - loss: 0.1454 - categorical_accuracy: 0.9474 - val_loss: 1.1936 - val_categorical_accuracy: 0.7926 - 484ms/epoch - 9ms/step
Epoch 400/1500
51/51 - 1s - loss: 0.1328 - categorical_accuracy: 0.9533 - val_loss: 1.2531 - val_categorical_accuracy: 0.7840 - 527ms/epoch - 10ms/step
Epoch 401/1500
51/51 - 0s - loss: 0.1449 - categorical_accuracy: 0.9466 - val_loss: 1.3701 - val_categorical_accuracy: 0.7940 - 498ms/epoch - 10ms/step
Epoch 402/1500
51/51 - 1s - loss: 0.2474 - categorical_accuracy: 0.9206 - val_loss: 1.1348 - val_categorical_accuracy: 0.8068 - 523ms/epoch - 10ms/step
Epoch 403/1500
51/51 - 0s - loss: 0.1367 - categorical_accuracy: 0.9501 - val_loss: 1.1981 - val_categorical_accuracy: 0.7995 - 494ms/epoch - 10ms/step
Epoch 404/1500
51/51 - 1s - loss: 0.1410 - categorical_accuracy: 0.9474 - val_loss: 1.2064 - val_categorical_accuracy: 0.7987 - 525ms/epoch - 10ms/step
Epoch 405/1500
51/51 - 0s - loss: 0.1318 - categorical_accuracy: 0.9530 - val_loss: 1.2480 - val_categorical_accuracy: 0.8025 - 477ms/epoch - 9ms/step
Epoch 406/1500
51/51 - 1s - loss: 0.1419 - categorical_accuracy: 0.9469 - val_loss: 1.2699 - val_categorical_accuracy: 0.7868 - 517ms/epoch - 10ms/step
Epoch 407/1500
51/51 - 0s - loss: 0.1414 - categorical_accuracy: 0.9495 - val_loss: 1.2548 - val_categorical_accuracy: 0.7967 - 492ms/epoch - 10ms/step
Epoch 408/1500
51/51 - 1s - loss: 0.1978 - categorical_accuracy: 0.9302 - val_loss: 1.2294 - val_categorical_accuracy: 0.7777 - 512ms/epoch - 10ms/step
Epoch 409/1500
51/51 - 1s - loss: 0.1510 - categorical_accuracy: 0.9443 - val_loss: 1.2055 - val_categorical_accuracy: 0.8002 - 503ms/epoch - 10ms/step
Epoch 410/1500
51/51 - 1s - loss: 0.1293 - categorical_accuracy: 0.9539 - val_loss: 1.2546 - val_categorical_accuracy: 0.7898 - 541ms/epoch - 11ms/step
Epoch 411/1500
51/51 - 0s - loss: 0.1428 - categorical_accuracy: 0.9467 - val_loss: 1.3132 - val_categorical_accuracy: 0.7954 - 496ms/epoch - 10ms/step
Epoch 412/1500
51/51 - 1s - loss: 0.1827 - categorical_accuracy: 0.9339 - val_loss: 1.3249 - val_categorical_accuracy: 0.7553 - 521ms/epoch - 10ms/step
Epoch 413/1500
51/51 - 1s - loss: 0.1797 - categorical_accuracy: 0.9340 - val_loss: 1.2605 - val_categorical_accuracy: 0.7869 - 527ms/epoch - 10ms/step
Epoch 414/1500
51/51 - 1s - loss: 0.1382 - categorical_accuracy: 0.9494 - val_loss: 1.3112 - val_categorical_accuracy: 0.8100 - 504ms/epoch - 10ms/step
Epoch 415/1500
51/51 - 1s - loss: 0.1351 - categorical_accuracy: 0.9488 - val_loss: 1.2892 - val_categorical_accuracy: 0.8042 - 520ms/epoch - 10ms/step
Epoch 416/1500
51/51 - 1s - loss: 0.1371 - categorical_accuracy: 0.9505 - val_loss: 1.3328 - val_categorical_accuracy: 0.7861 - 510ms/epoch - 10ms/step
Epoch 417/1500
51/51 - 0s - loss: 0.1320 - categorical_accuracy: 0.9514 - val_loss: 1.2800 - val_categorical_accuracy: 0.8009 - 495ms/epoch - 10ms/step
Epoch 418/1500
51/51 - 1s - loss: 0.1519 - categorical_accuracy: 0.9440 - val_loss: 1.3207 - val_categorical_accuracy: 0.8027 - 505ms/epoch - 10ms/step
Epoch 419/1500
51/51 - 1s - loss: 0.2574 - categorical_accuracy: 0.9213 - val_loss: 1.1462 - val_categorical_accuracy: 0.8020 - 521ms/epoch - 10ms/step
Epoch 420/1500
51/51 - 1s - loss: 0.1345 - categorical_accuracy: 0.9515 - val_loss: 1.2532 - val_categorical_accuracy: 0.8027 - 501ms/epoch - 10ms/step
Epoch 421/1500
51/51 - 1s - loss: 0.1300 - categorical_accuracy: 0.9524 - val_loss: 1.2781 - val_categorical_accuracy: 0.7830 - 513ms/epoch - 10ms/step
Epoch 422/1500
51/51 - 1s - loss: 0.1337 - categorical_accuracy: 0.9511 - val_loss: 1.2592 - val_categorical_accuracy: 0.7988 - 504ms/epoch - 10ms/step
Epoch 423/1500
51/51 - 1s - loss: 0.1388 - categorical_accuracy: 0.9485 - val_loss: 1.3101 - val_categorical_accuracy: 0.7727 - 503ms/epoch - 10ms/step
Epoch 424/1500
51/51 - 0s - loss: 0.1480 - categorical_accuracy: 0.9471 - val_loss: 1.4254 - val_categorical_accuracy: 0.7594 - 494ms/epoch - 10ms/step
Epoch 425/1500
51/51 - 1s - loss: 0.2228 - categorical_accuracy: 0.9256 - val_loss: 1.2868 - val_categorical_accuracy: 0.7912 - 508ms/epoch - 10ms/step
Epoch 426/1500
51/51 - 1s - loss: 0.1319 - categorical_accuracy: 0.9517 - val_loss: 1.2412 - val_categorical_accuracy: 0.7895 - 501ms/epoch - 10ms/step
Epoch 427/1500
51/51 - 1s - loss: 0.1224 - categorical_accuracy: 0.9568 - val_loss: 1.3319 - val_categorical_accuracy: 0.7903 - 531ms/epoch - 10ms/step
Epoch 428/1500
51/51 - 1s - loss: 0.1362 - categorical_accuracy: 0.9505 - val_loss: 1.2815 - val_categorical_accuracy: 0.7925 - 508ms/epoch - 10ms/step
Epoch 429/1500
51/51 - 1s - loss: 0.1275 - categorical_accuracy: 0.9525 - val_loss: 1.2861 - val_categorical_accuracy: 0.7981 - 539ms/epoch - 11ms/step
Epoch 430/1500
51/51 - 0s - loss: 0.1337 - categorical_accuracy: 0.9515 - val_loss: 1.3258 - val_categorical_accuracy: 0.7908 - 499ms/epoch - 10ms/step
Epoch 431/1500
51/51 - 1s - loss: 0.2098 - categorical_accuracy: 0.9322 - val_loss: 1.1756 - val_categorical_accuracy: 0.7995 - 519ms/epoch - 10ms/step
Epoch 432/1500
51/51 - 0s - loss: 0.1351 - categorical_accuracy: 0.9498 - val_loss: 1.2905 - val_categorical_accuracy: 0.8041 - 490ms/epoch - 10ms/step
Epoch 433/1500
51/51 - 1s - loss: 0.1314 - categorical_accuracy: 0.9512 - val_loss: 1.3690 - val_categorical_accuracy: 0.7856 - 545ms/epoch - 11ms/step
Epoch 434/1500
51/51 - 0s - loss: 0.1291 - categorical_accuracy: 0.9530 - val_loss: 1.3312 - val_categorical_accuracy: 0.8066 - 489ms/epoch - 10ms/step
Epoch 435/1500
51/51 - 1s - loss: 0.1316 - categorical_accuracy: 0.9513 - val_loss: 1.3978 - val_categorical_accuracy: 0.8085 - 537ms/epoch - 11ms/step
Epoch 436/1500
51/51 - 1s - loss: 0.1437 - categorical_accuracy: 0.9478 - val_loss: 1.6850 - val_categorical_accuracy: 0.7906 - 543ms/epoch - 11ms/step
Epoch 437/1500
51/51 - 1s - loss: 0.2312 - categorical_accuracy: 0.9280 - val_loss: 1.2413 - val_categorical_accuracy: 0.7997 - 602ms/epoch - 12ms/step
Epoch 438/1500
51/51 - 1s - loss: 0.1293 - categorical_accuracy: 0.9539 - val_loss: 1.7396 - val_categorical_accuracy: 0.7899 - 557ms/epoch - 11ms/step
Epoch 439/1500
51/51 - 1s - loss: 0.1685 - categorical_accuracy: 0.9412 - val_loss: 1.2466 - val_categorical_accuracy: 0.7933 - 553ms/epoch - 11ms/step
Epoch 440/1500
51/51 - 1s - loss: 0.1261 - categorical_accuracy: 0.9547 - val_loss: 1.2886 - val_categorical_accuracy: 0.7945 - 550ms/epoch - 11ms/step
Epoch 441/1500
51/51 - 1s - loss: 0.1230 - categorical_accuracy: 0.9557 - val_loss: 1.4065 - val_categorical_accuracy: 0.8060 - 522ms/epoch - 10ms/step
Epoch 442/1500
51/51 - 1s - loss: 0.1355 - categorical_accuracy: 0.9515 - val_loss: 1.3592 - val_categorical_accuracy: 0.8080 - 562ms/epoch - 11ms/step
Epoch 443/1500
51/51 - 1s - loss: 0.1316 - categorical_accuracy: 0.9512 - val_loss: 1.2970 - val_categorical_accuracy: 0.8059 - 554ms/epoch - 11ms/step
Epoch 444/1500
51/51 - 1s - loss: 0.1293 - categorical_accuracy: 0.9528 - val_loss: 1.3529 - val_categorical_accuracy: 0.7873 - 565ms/epoch - 11ms/step
Epoch 445/1500
51/51 - 1s - loss: 0.1307 - categorical_accuracy: 0.9525 - val_loss: 1.3672 - val_categorical_accuracy: 0.7871 - 538ms/epoch - 11ms/step
Epoch 446/1500
51/51 - 1s - loss: 0.2217 - categorical_accuracy: 0.9278 - val_loss: 1.2322 - val_categorical_accuracy: 0.7957 - 555ms/epoch - 11ms/step
Epoch 447/1500
51/51 - 1s - loss: 0.1251 - categorical_accuracy: 0.9538 - val_loss: 1.3044 - val_categorical_accuracy: 0.7986 - 544ms/epoch - 11ms/step
Epoch 448/1500
51/51 - 1s - loss: 0.1220 - categorical_accuracy: 0.9547 - val_loss: 1.3812 - val_categorical_accuracy: 0.7905 - 566ms/epoch - 11ms/step
Epoch 449/1500
51/51 - 1s - loss: 0.1280 - categorical_accuracy: 0.9537 - val_loss: 1.3456 - val_categorical_accuracy: 0.7986 - 557ms/epoch - 11ms/step
Epoch 450/1500
51/51 - 1s - loss: 0.1210 - categorical_accuracy: 0.9556 - val_loss: 1.3476 - val_categorical_accuracy: 0.8051 - 550ms/epoch - 11ms/step
Epoch 451/1500
51/51 - 1s - loss: 0.1307 - categorical_accuracy: 0.9522 - val_loss: 1.3390 - val_categorical_accuracy: 0.8091 - 566ms/epoch - 11ms/step
Epoch 452/1500
51/51 - 1s - loss: 0.1236 - categorical_accuracy: 0.9543 - val_loss: 1.3632 - val_categorical_accuracy: 0.7940 - 517ms/epoch - 10ms/step
Epoch 453/1500
51/51 - 1s - loss: 0.1521 - categorical_accuracy: 0.9448 - val_loss: 1.3080 - val_categorical_accuracy: 0.7921 - 572ms/epoch - 11ms/step
Epoch 454/1500
51/51 - 1s - loss: 0.1576 - categorical_accuracy: 0.9425 - val_loss: 1.3788 - val_categorical_accuracy: 0.7835 - 522ms/epoch - 10ms/step
Epoch 455/1500
51/51 - 1s - loss: 0.1892 - categorical_accuracy: 0.9380 - val_loss: 1.2248 - val_categorical_accuracy: 0.7869 - 572ms/epoch - 11ms/step
Epoch 456/1500
51/51 - 1s - loss: 0.1465 - categorical_accuracy: 0.9457 - val_loss: 1.2866 - val_categorical_accuracy: 0.7929 - 540ms/epoch - 11ms/step
Epoch 457/1500
51/51 - 1s - loss: 0.2063 - categorical_accuracy: 0.9346 - val_loss: 1.1302 - val_categorical_accuracy: 0.7825 - 557ms/epoch - 11ms/step
Epoch 458/1500
51/51 - 1s - loss: 0.1431 - categorical_accuracy: 0.9484 - val_loss: 1.2962 - val_categorical_accuracy: 0.7871 - 534ms/epoch - 10ms/step
Epoch 459/1500
51/51 - 1s - loss: 0.1294 - categorical_accuracy: 0.9519 - val_loss: 1.3192 - val_categorical_accuracy: 0.8030 - 535ms/epoch - 10ms/step
Epoch 460/1500
51/51 - 1s - loss: 0.1204 - categorical_accuracy: 0.9564 - val_loss: 1.3176 - val_categorical_accuracy: 0.7971 - 566ms/epoch - 11ms/step
Epoch 461/1500
51/51 - 1s - loss: 0.1394 - categorical_accuracy: 0.9483 - val_loss: 1.3631 - val_categorical_accuracy: 0.7927 - 513ms/epoch - 10ms/step
Epoch 462/1500
51/51 - 1s - loss: 0.1257 - categorical_accuracy: 0.9533 - val_loss: 1.3952 - val_categorical_accuracy: 0.7954 - 510ms/epoch - 10ms/step
Epoch 463/1500
51/51 - 0s - loss: 0.1237 - categorical_accuracy: 0.9554 - val_loss: 1.3616 - val_categorical_accuracy: 0.8035 - 495ms/epoch - 10ms/step
Epoch 464/1500
51/51 - 1s - loss: 0.1236 - categorical_accuracy: 0.9549 - val_loss: 1.3435 - val_categorical_accuracy: 0.7950 - 524ms/epoch - 10ms/step
Epoch 465/1500
51/51 - 0s - loss: 0.1227 - categorical_accuracy: 0.9552 - val_loss: 1.4212 - val_categorical_accuracy: 0.8063 - 492ms/epoch - 10ms/step
Epoch 466/1500
51/51 - 1s - loss: 0.1237 - categorical_accuracy: 0.9552 - val_loss: 1.3838 - val_categorical_accuracy: 0.7986 - 576ms/epoch - 11ms/step
Epoch 467/1500
51/51 - 0s - loss: 0.1246 - categorical_accuracy: 0.9546 - val_loss: 1.4255 - val_categorical_accuracy: 0.7901 - 481ms/epoch - 9ms/step
Epoch 468/1500
51/51 - 1s - loss: 0.1253 - categorical_accuracy: 0.9537 - val_loss: 1.4971 - val_categorical_accuracy: 0.7806 - 523ms/epoch - 10ms/step
Epoch 469/1500
51/51 - 0s - loss: 0.1568 - categorical_accuracy: 0.9425 - val_loss: 1.3577 - val_categorical_accuracy: 0.8064 - 477ms/epoch - 9ms/step
Epoch 470/1500
51/51 - 1s - loss: 0.1161 - categorical_accuracy: 0.9575 - val_loss: 1.3516 - val_categorical_accuracy: 0.7972 - 513ms/epoch - 10ms/step
Epoch 471/1500
51/51 - 0s - loss: 0.1239 - categorical_accuracy: 0.9554 - val_loss: 1.3754 - val_categorical_accuracy: 0.8005 - 489ms/epoch - 10ms/step
Epoch 472/1500
51/51 - 1s - loss: 0.1141 - categorical_accuracy: 0.9583 - val_loss: 1.4494 - val_categorical_accuracy: 0.8050 - 536ms/epoch - 11ms/step
Epoch 473/1500
51/51 - 0s - loss: 0.1943 - categorical_accuracy: 0.9395 - val_loss: 1.2559 - val_categorical_accuracy: 0.7909 - 489ms/epoch - 10ms/step
Epoch 474/1500
51/51 - 1s - loss: 0.1288 - categorical_accuracy: 0.9524 - val_loss: 1.3545 - val_categorical_accuracy: 0.8056 - 516ms/epoch - 10ms/step
Epoch 475/1500
51/51 - 0s - loss: 0.1161 - categorical_accuracy: 0.9576 - val_loss: 1.4125 - val_categorical_accuracy: 0.7939 - 477ms/epoch - 9ms/step
Epoch 476/1500
51/51 - 0s - loss: 0.2202 - categorical_accuracy: 0.9289 - val_loss: 1.3021 - val_categorical_accuracy: 0.8057 - 493ms/epoch - 10ms/step
Epoch 477/1500
51/51 - 0s - loss: 0.1167 - categorical_accuracy: 0.9569 - val_loss: 1.3881 - val_categorical_accuracy: 0.8081 - 479ms/epoch - 9ms/step
Epoch 478/1500
51/51 - 1s - loss: 0.1150 - categorical_accuracy: 0.9578 - val_loss: 1.3764 - val_categorical_accuracy: 0.8030 - 539ms/epoch - 11ms/step
Epoch 479/1500
51/51 - 0s - loss: 0.1217 - categorical_accuracy: 0.9548 - val_loss: 1.4523 - val_categorical_accuracy: 0.7858 - 492ms/epoch - 10ms/step
Epoch 480/1500
51/51 - 1s - loss: 0.1235 - categorical_accuracy: 0.9549 - val_loss: 1.5114 - val_categorical_accuracy: 0.8090 - 534ms/epoch - 10ms/step
Epoch 481/1500
51/51 - 0s - loss: 0.1297 - categorical_accuracy: 0.9524 - val_loss: 1.4018 - val_categorical_accuracy: 0.7994 - 476ms/epoch - 9ms/step
Epoch 482/1500
51/51 - 1s - loss: 0.1287 - categorical_accuracy: 0.9529 - val_loss: 1.4329 - val_categorical_accuracy: 0.8046 - 506ms/epoch - 10ms/step
Epoch 483/1500
51/51 - 0s - loss: 0.2437 - categorical_accuracy: 0.9260 - val_loss: 1.2733 - val_categorical_accuracy: 0.8058 - 488ms/epoch - 10ms/step
Epoch 484/1500
51/51 - 1s - loss: 0.1196 - categorical_accuracy: 0.9561 - val_loss: 1.3481 - val_categorical_accuracy: 0.7901 - 522ms/epoch - 10ms/step
Epoch 485/1500
51/51 - 0s - loss: 0.1138 - categorical_accuracy: 0.9598 - val_loss: 1.3693 - val_categorical_accuracy: 0.8062 - 488ms/epoch - 10ms/step
Epoch 486/1500
51/51 - 1s - loss: 0.1147 - categorical_accuracy: 0.9594 - val_loss: 1.4396 - val_categorical_accuracy: 0.7935 - 567ms/epoch - 11ms/step
Epoch 487/1500
51/51 - 0s - loss: 0.1136 - categorical_accuracy: 0.9590 - val_loss: 1.4498 - val_categorical_accuracy: 0.8043 - 488ms/epoch - 10ms/step
Epoch 488/1500
51/51 - 1s - loss: 0.1184 - categorical_accuracy: 0.9575 - val_loss: 1.4936 - val_categorical_accuracy: 0.7950 - 505ms/epoch - 10ms/step
Epoch 489/1500
51/51 - 0s - loss: 0.1249 - categorical_accuracy: 0.9540 - val_loss: 1.4110 - val_categorical_accuracy: 0.8075 - 489ms/epoch - 10ms/step
Epoch 490/1500
51/51 - 1s - loss: 0.1168 - categorical_accuracy: 0.9578 - val_loss: 1.4510 - val_categorical_accuracy: 0.7986 - 512ms/epoch - 10ms/step
Epoch 491/1500
51/51 - 0s - loss: 0.1149 - categorical_accuracy: 0.9588 - val_loss: 1.4536 - val_categorical_accuracy: 0.7978 - 498ms/epoch - 10ms/step
Epoch 492/1500
51/51 - 1s - loss: 0.1177 - categorical_accuracy: 0.9560 - val_loss: 1.4545 - val_categorical_accuracy: 0.8051 - 519ms/epoch - 10ms/step
Epoch 493/1500
51/51 - 1s - loss: 0.1449 - categorical_accuracy: 0.9470 - val_loss: 1.9082 - val_categorical_accuracy: 0.7988 - 504ms/epoch - 10ms/step
Epoch 494/1500
51/51 - 1s - loss: 0.2267 - categorical_accuracy: 0.9266 - val_loss: 1.3014 - val_categorical_accuracy: 0.8046 - 504ms/epoch - 10ms/step
Epoch 495/1500
51/51 - 0s - loss: 0.1186 - categorical_accuracy: 0.9561 - val_loss: 1.3831 - val_categorical_accuracy: 0.7928 - 492ms/epoch - 10ms/step
Epoch 496/1500
51/51 - 1s - loss: 0.1106 - categorical_accuracy: 0.9605 - val_loss: 1.4210 - val_categorical_accuracy: 0.8043 - 510ms/epoch - 10ms/step
Epoch 497/1500
51/51 - 1s - loss: 0.1182 - categorical_accuracy: 0.9578 - val_loss: 1.4026 - val_categorical_accuracy: 0.7989 - 504ms/epoch - 10ms/step
Epoch 498/1500
51/51 - 1s - loss: 0.1162 - categorical_accuracy: 0.9578 - val_loss: 1.4606 - val_categorical_accuracy: 0.8010 - 510ms/epoch - 10ms/step
Epoch 499/1500
51/51 - 0s - loss: 0.1126 - categorical_accuracy: 0.9582 - val_loss: 1.5921 - val_categorical_accuracy: 0.7724 - 488ms/epoch - 10ms/step
Epoch 500/1500
51/51 - 1s - loss: 0.2843 - categorical_accuracy: 0.9125 - val_loss: 1.2407 - val_categorical_accuracy: 0.7917 - 524ms/epoch - 10ms/step
Epoch 501/1500
51/51 - 0s - loss: 0.1255 - categorical_accuracy: 0.9545 - val_loss: 1.3425 - val_categorical_accuracy: 0.8079 - 489ms/epoch - 10ms/step
Epoch 502/1500
51/51 - 0s - loss: 0.1159 - categorical_accuracy: 0.9586 - val_loss: 1.4641 - val_categorical_accuracy: 0.7890 - 495ms/epoch - 10ms/step
Epoch 503/1500
51/51 - 1s - loss: 0.1246 - categorical_accuracy: 0.9552 - val_loss: 1.4033 - val_categorical_accuracy: 0.7987 - 521ms/epoch - 10ms/step
Epoch 504/1500
51/51 - 1s - loss: 0.1094 - categorical_accuracy: 0.9601 - val_loss: 1.4497 - val_categorical_accuracy: 0.8088 - 510ms/epoch - 10ms/step
Epoch 505/1500
51/51 - 1s - loss: 0.2731 - categorical_accuracy: 0.9191 - val_loss: 1.2916 - val_categorical_accuracy: 0.8031 - 516ms/epoch - 10ms/step
Epoch 506/1500
51/51 - 0s - loss: 0.1141 - categorical_accuracy: 0.9594 - val_loss: 1.3601 - val_categorical_accuracy: 0.8021 - 492ms/epoch - 10ms/step
Epoch 507/1500
51/51 - 0s - loss: 0.1102 - categorical_accuracy: 0.9597 - val_loss: 1.3808 - val_categorical_accuracy: 0.8072 - 492ms/epoch - 10ms/step
Epoch 508/1500
51/51 - 1s - loss: 0.1184 - categorical_accuracy: 0.9576 - val_loss: 1.7821 - val_categorical_accuracy: 0.6978 - 500ms/epoch - 10ms/step
Epoch 509/1500
51/51 - 1s - loss: 0.1953 - categorical_accuracy: 0.9380 - val_loss: 1.3586 - val_categorical_accuracy: 0.8054 - 521ms/epoch - 10ms/step
Epoch 510/1500
51/51 - 1s - loss: 0.1087 - categorical_accuracy: 0.9595 - val_loss: 1.3950 - val_categorical_accuracy: 0.8017 - 502ms/epoch - 10ms/step
Epoch 511/1500
51/51 - 0s - loss: 0.1091 - categorical_accuracy: 0.9609 - val_loss: 1.4016 - val_categorical_accuracy: 0.7946 - 490ms/epoch - 10ms/step
Epoch 512/1500
51/51 - 1s - loss: 0.1102 - categorical_accuracy: 0.9595 - val_loss: 1.4181 - val_categorical_accuracy: 0.7890 - 504ms/epoch - 10ms/step
Epoch 513/1500
51/51 - 1s - loss: 0.1164 - categorical_accuracy: 0.9573 - val_loss: 1.4687 - val_categorical_accuracy: 0.8026 - 508ms/epoch - 10ms/step
Epoch 514/1500
51/51 - 0s - loss: 0.1058 - categorical_accuracy: 0.9610 - val_loss: 1.4826 - val_categorical_accuracy: 0.7995 - 492ms/epoch - 10ms/step
Epoch 515/1500
51/51 - 1s - loss: 0.1233 - categorical_accuracy: 0.9544 - val_loss: 1.4434 - val_categorical_accuracy: 0.8051 - 526ms/epoch - 10ms/step
Epoch 516/1500
51/51 - 1s - loss: 0.1136 - categorical_accuracy: 0.9564 - val_loss: 1.4468 - val_categorical_accuracy: 0.7982 - 510ms/epoch - 10ms/step
Epoch 517/1500
51/51 - 0s - loss: 0.1075 - categorical_accuracy: 0.9594 - val_loss: 1.4599 - val_categorical_accuracy: 0.7896 - 492ms/epoch - 10ms/step
Epoch 518/1500
51/51 - 1s - loss: 0.1120 - categorical_accuracy: 0.9599 - val_loss: 1.4851 - val_categorical_accuracy: 0.8047 - 507ms/epoch - 10ms/step
Epoch 519/1500
51/51 - 1s - loss: 0.1130 - categorical_accuracy: 0.9595 - val_loss: 1.5289 - val_categorical_accuracy: 0.7943 - 504ms/epoch - 10ms/step
Epoch 520/1500
51/51 - 0s - loss: 0.1175 - categorical_accuracy: 0.9573 - val_loss: 1.4822 - val_categorical_accuracy: 0.8030 - 493ms/epoch - 10ms/step
Epoch 521/1500
51/51 - 1s - loss: 0.1127 - categorical_accuracy: 0.9585 - val_loss: 1.4853 - val_categorical_accuracy: 0.7863 - 510ms/epoch - 10ms/step
Epoch 522/1500
51/51 - 1s - loss: 0.1123 - categorical_accuracy: 0.9578 - val_loss: 1.5343 - val_categorical_accuracy: 0.7957 - 791ms/epoch - 16ms/step
Epoch 523/1500
51/51 - 1s - loss: 0.1105 - categorical_accuracy: 0.9586 - val_loss: 1.4861 - val_categorical_accuracy: 0.8050 - 540ms/epoch - 11ms/step
Epoch 524/1500
51/51 - 1s - loss: 0.1899 - categorical_accuracy: 0.9395 - val_loss: 1.7927 - val_categorical_accuracy: 0.6571 - 516ms/epoch - 10ms/step
Epoch 525/1500
51/51 - 1s - loss: 0.1899 - categorical_accuracy: 0.9357 - val_loss: 1.3751 - val_categorical_accuracy: 0.8034 - 521ms/epoch - 10ms/step
Epoch 526/1500
51/51 - 1s - loss: 0.1166 - categorical_accuracy: 0.9572 - val_loss: 1.4346 - val_categorical_accuracy: 0.8042 - 524ms/epoch - 10ms/step
Epoch 527/1500
51/51 - 1s - loss: 0.1086 - categorical_accuracy: 0.9612 - val_loss: 1.5029 - val_categorical_accuracy: 0.7817 - 522ms/epoch - 10ms/step
Epoch 528/1500
51/51 - 1s - loss: 0.1181 - categorical_accuracy: 0.9576 - val_loss: 1.4440 - val_categorical_accuracy: 0.7996 - 540ms/epoch - 11ms/step
Epoch 529/1500
51/51 - 1s - loss: 0.1401 - categorical_accuracy: 0.9496 - val_loss: 1.4409 - val_categorical_accuracy: 0.8025 - 522ms/epoch - 10ms/step
Epoch 530/1500
51/51 - 1s - loss: 0.1112 - categorical_accuracy: 0.9587 - val_loss: 1.4852 - val_categorical_accuracy: 0.7915 - 525ms/epoch - 10ms/step
Epoch 531/1500
51/51 - 1s - loss: 0.1192 - categorical_accuracy: 0.9567 - val_loss: 1.4561 - val_categorical_accuracy: 0.7949 - 517ms/epoch - 10ms/step
Epoch 532/1500
51/51 - 1s - loss: 0.1028 - categorical_accuracy: 0.9625 - val_loss: 1.4565 - val_categorical_accuracy: 0.8022 - 545ms/epoch - 11ms/step
Epoch 533/1500
51/51 - 1s - loss: 0.2092 - categorical_accuracy: 0.9299 - val_loss: 1.3879 - val_categorical_accuracy: 0.7988 - 526ms/epoch - 10ms/step
Epoch 534/1500
51/51 - 1s - loss: 0.1211 - categorical_accuracy: 0.9557 - val_loss: 1.4612 - val_categorical_accuracy: 0.7991 - 539ms/epoch - 11ms/step
Epoch 535/1500
51/51 - 0s - loss: 0.1132 - categorical_accuracy: 0.9585 - val_loss: 1.4886 - val_categorical_accuracy: 0.8044 - 492ms/epoch - 10ms/step
Epoch 536/1500
51/51 - 1s - loss: 0.1160 - categorical_accuracy: 0.9580 - val_loss: 1.4250 - val_categorical_accuracy: 0.8057 - 521ms/epoch - 10ms/step
Epoch 537/1500
51/51 - 0s - loss: 0.1039 - categorical_accuracy: 0.9622 - val_loss: 1.4964 - val_categorical_accuracy: 0.7969 - 489ms/epoch - 10ms/step
Epoch 538/1500
51/51 - 1s - loss: 0.1043 - categorical_accuracy: 0.9616 - val_loss: 1.5734 - val_categorical_accuracy: 0.8058 - 565ms/epoch - 11ms/step
Epoch 539/1500
51/51 - 1s - loss: 0.1104 - categorical_accuracy: 0.9591 - val_loss: 1.5246 - val_categorical_accuracy: 0.8082 - 505ms/epoch - 10ms/step
Epoch 540/1500
51/51 - 1s - loss: 0.1270 - categorical_accuracy: 0.9545 - val_loss: 1.4815 - val_categorical_accuracy: 0.7693 - 572ms/epoch - 11ms/step
Epoch 541/1500
51/51 - 1s - loss: 0.2239 - categorical_accuracy: 0.9285 - val_loss: 1.4400 - val_categorical_accuracy: 0.7953 - 550ms/epoch - 11ms/step
Epoch 542/1500
51/51 - 1s - loss: 0.1179 - categorical_accuracy: 0.9562 - val_loss: 1.4233 - val_categorical_accuracy: 0.7894 - 553ms/epoch - 11ms/step
Epoch 543/1500
51/51 - 1s - loss: 0.1153 - categorical_accuracy: 0.9571 - val_loss: 1.4978 - val_categorical_accuracy: 0.7840 - 617ms/epoch - 12ms/step
Epoch 544/1500
51/51 - 1s - loss: 0.1062 - categorical_accuracy: 0.9600 - val_loss: 1.5426 - val_categorical_accuracy: 0.8077 - 551ms/epoch - 11ms/step
Epoch 545/1500
51/51 - 1s - loss: 0.1076 - categorical_accuracy: 0.9611 - val_loss: 1.5581 - val_categorical_accuracy: 0.7812 - 597ms/epoch - 12ms/step
Epoch 546/1500
51/51 - 1s - loss: 0.3967 - categorical_accuracy: 0.8955 - val_loss: 1.2163 - val_categorical_accuracy: 0.7965 - 556ms/epoch - 11ms/step
Epoch 547/1500
51/51 - 1s - loss: 0.1127 - categorical_accuracy: 0.9610 - val_loss: 1.3189 - val_categorical_accuracy: 0.8024 - 543ms/epoch - 11ms/step
Epoch 548/1500
51/51 - 1s - loss: 0.1083 - categorical_accuracy: 0.9607 - val_loss: 1.3821 - val_categorical_accuracy: 0.8013 - 589ms/epoch - 12ms/step
Epoch 549/1500
51/51 - 1s - loss: 0.1016 - categorical_accuracy: 0.9633 - val_loss: 1.4407 - val_categorical_accuracy: 0.8036 - 583ms/epoch - 11ms/step
Epoch 550/1500
51/51 - 1s - loss: 0.1019 - categorical_accuracy: 0.9627 - val_loss: 1.4664 - val_categorical_accuracy: 0.7968 - 591ms/epoch - 12ms/step
Epoch 551/1500
51/51 - 1s - loss: 0.1047 - categorical_accuracy: 0.9612 - val_loss: 1.4699 - val_categorical_accuracy: 0.7971 - 558ms/epoch - 11ms/step
Epoch 552/1500
51/51 - 1s - loss: 0.1004 - categorical_accuracy: 0.9638 - val_loss: 1.4663 - val_categorical_accuracy: 0.8021 - 586ms/epoch - 11ms/step
Epoch 553/1500
51/51 - 1s - loss: 0.1038 - categorical_accuracy: 0.9619 - val_loss: 1.5023 - val_categorical_accuracy: 0.7857 - 553ms/epoch - 11ms/step
Epoch 554/1500
51/51 - 1s - loss: 0.1135 - categorical_accuracy: 0.9586 - val_loss: 1.5301 - val_categorical_accuracy: 0.8029 - 584ms/epoch - 11ms/step
Epoch 555/1500
51/51 - 1s - loss: 0.1083 - categorical_accuracy: 0.9603 - val_loss: 1.5320 - val_categorical_accuracy: 0.8073 - 555ms/epoch - 11ms/step
Epoch 556/1500
51/51 - 1s - loss: 0.1055 - categorical_accuracy: 0.9598 - val_loss: 1.5094 - val_categorical_accuracy: 0.7982 - 575ms/epoch - 11ms/step
Epoch 557/1500
51/51 - 1s - loss: 0.1077 - categorical_accuracy: 0.9608 - val_loss: 1.5426 - val_categorical_accuracy: 0.8064 - 550ms/epoch - 11ms/step
Epoch 558/1500
51/51 - 1s - loss: 0.1117 - categorical_accuracy: 0.9583 - val_loss: 1.5994 - val_categorical_accuracy: 0.7795 - 538ms/epoch - 11ms/step
Epoch 559/1500
51/51 - 1s - loss: 0.1122 - categorical_accuracy: 0.9590 - val_loss: 1.5756 - val_categorical_accuracy: 0.7909 - 580ms/epoch - 11ms/step
Epoch 560/1500
51/51 - 1s - loss: 0.1058 - categorical_accuracy: 0.9617 - val_loss: 1.5541 - val_categorical_accuracy: 0.8003 - 543ms/epoch - 11ms/step
Epoch 561/1500
51/51 - 1s - loss: 0.1102 - categorical_accuracy: 0.9591 - val_loss: 1.5096 - val_categorical_accuracy: 0.7969 - 618ms/epoch - 12ms/step
Epoch 562/1500
51/51 - 1s - loss: 0.1094 - categorical_accuracy: 0.9593 - val_loss: 1.5297 - val_categorical_accuracy: 0.7846 - 556ms/epoch - 11ms/step
Epoch 563/1500
51/51 - 1s - loss: 0.1034 - categorical_accuracy: 0.9625 - val_loss: 1.6054 - val_categorical_accuracy: 0.8047 - 569ms/epoch - 11ms/step
Epoch 564/1500
51/51 - 1s - loss: 0.0998 - categorical_accuracy: 0.9636 - val_loss: 1.5534 - val_categorical_accuracy: 0.7967 - 570ms/epoch - 11ms/step
Epoch 565/1500
51/51 - 1s - loss: 0.1073 - categorical_accuracy: 0.9618 - val_loss: 1.6159 - val_categorical_accuracy: 0.8015 - 555ms/epoch - 11ms/step
Epoch 566/1500
51/51 - 1s - loss: 0.1294 - categorical_accuracy: 0.9533 - val_loss: 1.5796 - val_categorical_accuracy: 0.7729 - 540ms/epoch - 11ms/step
Epoch 567/1500
51/51 - 1s - loss: 0.1177 - categorical_accuracy: 0.9558 - val_loss: 1.5560 - val_categorical_accuracy: 0.7960 - 508ms/epoch - 10ms/step
Epoch 568/1500
51/51 - 1s - loss: 0.1975 - categorical_accuracy: 0.9396 - val_loss: 1.3218 - val_categorical_accuracy: 0.7601 - 553ms/epoch - 11ms/step
Epoch 569/1500
51/51 - 0s - loss: 0.1508 - categorical_accuracy: 0.9454 - val_loss: 1.4489 - val_categorical_accuracy: 0.7991 - 491ms/epoch - 10ms/step
Epoch 570/1500
51/51 - 1s - loss: 0.1207 - categorical_accuracy: 0.9557 - val_loss: 1.4827 - val_categorical_accuracy: 0.7993 - 541ms/epoch - 11ms/step
Epoch 571/1500
51/51 - 1s - loss: 0.1079 - categorical_accuracy: 0.9602 - val_loss: 1.5043 - val_categorical_accuracy: 0.7952 - 507ms/epoch - 10ms/step
Epoch 572/1500
51/51 - 1s - loss: 0.1070 - categorical_accuracy: 0.9600 - val_loss: 1.5829 - val_categorical_accuracy: 0.8053 - 521ms/epoch - 10ms/step
Epoch 573/1500
51/51 - 1s - loss: 0.1024 - categorical_accuracy: 0.9619 - val_loss: 1.6511 - val_categorical_accuracy: 0.8037 - 514ms/epoch - 10ms/step
Epoch 574/1500
51/51 - 1s - loss: 0.1077 - categorical_accuracy: 0.9593 - val_loss: 1.5748 - val_categorical_accuracy: 0.7950 - 528ms/epoch - 10ms/step
Epoch 575/1500
51/51 - 0s - loss: 0.3940 - categorical_accuracy: 0.8968 - val_loss: 1.2488 - val_categorical_accuracy: 0.8007 - 493ms/epoch - 10ms/step
Epoch 576/1500
51/51 - 1s - loss: 0.1120 - categorical_accuracy: 0.9597 - val_loss: 1.3984 - val_categorical_accuracy: 0.8033 - 535ms/epoch - 10ms/step
Epoch 577/1500
51/51 - 1s - loss: 0.1014 - categorical_accuracy: 0.9629 - val_loss: 1.4562 - val_categorical_accuracy: 0.8010 - 507ms/epoch - 10ms/step
Epoch 578/1500
51/51 - 1s - loss: 0.1037 - categorical_accuracy: 0.9622 - val_loss: 1.5392 - val_categorical_accuracy: 0.7918 - 542ms/epoch - 11ms/step
Epoch 579/1500
51/51 - 1s - loss: 0.1014 - categorical_accuracy: 0.9639 - val_loss: 1.5113 - val_categorical_accuracy: 0.8024 - 534ms/epoch - 10ms/step
Epoch 580/1500
51/51 - 1s - loss: 0.0968 - categorical_accuracy: 0.9636 - val_loss: 1.5019 - val_categorical_accuracy: 0.7998 - 532ms/epoch - 10ms/step
Epoch 581/1500
51/51 - 1s - loss: 0.0990 - categorical_accuracy: 0.9641 - val_loss: 1.5357 - val_categorical_accuracy: 0.7975 - 508ms/epoch - 10ms/step
Epoch 582/1500
51/51 - 1s - loss: 0.1069 - categorical_accuracy: 0.9611 - val_loss: 1.5200 - val_categorical_accuracy: 0.8007 - 508ms/epoch - 10ms/step
Epoch 583/1500
51/51 - 1s - loss: 0.0992 - categorical_accuracy: 0.9635 - val_loss: 1.5634 - val_categorical_accuracy: 0.8010 - 536ms/epoch - 11ms/step
Epoch 584/1500
51/51 - 1s - loss: 0.1002 - categorical_accuracy: 0.9630 - val_loss: 1.5371 - val_categorical_accuracy: 0.7934 - 510ms/epoch - 10ms/step
Epoch 585/1500
51/51 - 1s - loss: 0.1080 - categorical_accuracy: 0.9606 - val_loss: 1.5742 - val_categorical_accuracy: 0.8070 - 537ms/epoch - 11ms/step
Epoch 586/1500
51/51 - 0s - loss: 0.1054 - categorical_accuracy: 0.9607 - val_loss: 1.6485 - val_categorical_accuracy: 0.8009 - 494ms/epoch - 10ms/step
Epoch 587/1500
51/51 - 1s - loss: 0.0995 - categorical_accuracy: 0.9635 - val_loss: 1.6559 - val_categorical_accuracy: 0.8064 - 532ms/epoch - 10ms/step
Epoch 588/1500
51/51 - 1s - loss: 0.0992 - categorical_accuracy: 0.9637 - val_loss: 1.6821 - val_categorical_accuracy: 0.7806 - 520ms/epoch - 10ms/step
Epoch 589/1500
51/51 - 1s - loss: 0.2257 - categorical_accuracy: 0.9314 - val_loss: 1.4621 - val_categorical_accuracy: 0.7930 - 541ms/epoch - 11ms/step
Epoch 590/1500
51/51 - 0s - loss: 0.1029 - categorical_accuracy: 0.9627 - val_loss: 1.6415 - val_categorical_accuracy: 0.7926 - 495ms/epoch - 10ms/step
Epoch 591/1500
51/51 - 1s - loss: 0.1022 - categorical_accuracy: 0.9640 - val_loss: 1.5259 - val_categorical_accuracy: 0.7876 - 549ms/epoch - 11ms/step
Epoch 592/1500
51/51 - 0s - loss: 0.1004 - categorical_accuracy: 0.9629 - val_loss: 1.6172 - val_categorical_accuracy: 0.8040 - 495ms/epoch - 10ms/step
Epoch 593/1500
51/51 - 1s - loss: 0.0991 - categorical_accuracy: 0.9638 - val_loss: 1.6053 - val_categorical_accuracy: 0.8071 - 541ms/epoch - 11ms/step
Epoch 594/1500
51/51 - 0s - loss: 0.1408 - categorical_accuracy: 0.9513 - val_loss: 1.7486 - val_categorical_accuracy: 0.7496 - 491ms/epoch - 10ms/step
Epoch 595/1500
51/51 - 1s - loss: 0.1500 - categorical_accuracy: 0.9464 - val_loss: 1.4963 - val_categorical_accuracy: 0.8046 - 536ms/epoch - 11ms/step
Epoch 596/1500
51/51 - 1s - loss: 0.1202 - categorical_accuracy: 0.9560 - val_loss: 1.4692 - val_categorical_accuracy: 0.7962 - 502ms/epoch - 10ms/step
Epoch 597/1500
51/51 - 1s - loss: 0.1013 - categorical_accuracy: 0.9626 - val_loss: 1.6501 - val_categorical_accuracy: 0.7759 - 539ms/epoch - 11ms/step
Epoch 598/1500
51/51 - 1s - loss: 0.0997 - categorical_accuracy: 0.9629 - val_loss: 1.6607 - val_categorical_accuracy: 0.7969 - 532ms/epoch - 10ms/step
Epoch 599/1500
51/51 - 1s - loss: 0.0983 - categorical_accuracy: 0.9640 - val_loss: 1.5971 - val_categorical_accuracy: 0.8056 - 538ms/epoch - 11ms/step
Epoch 600/1500
51/51 - 1s - loss: 0.1002 - categorical_accuracy: 0.9630 - val_loss: 1.5703 - val_categorical_accuracy: 0.7937 - 508ms/epoch - 10ms/step
Epoch 601/1500
51/51 - 1s - loss: 0.1013 - categorical_accuracy: 0.9626 - val_loss: 1.5833 - val_categorical_accuracy: 0.7852 - 506ms/epoch - 10ms/step
Epoch 602/1500
51/51 - 1s - loss: 0.0993 - categorical_accuracy: 0.9637 - val_loss: 1.5636 - val_categorical_accuracy: 0.7958 - 508ms/epoch - 10ms/step
Epoch 603/1500
51/51 - 1s - loss: 0.0952 - categorical_accuracy: 0.9634 - val_loss: 1.6067 - val_categorical_accuracy: 0.8019 - 537ms/epoch - 11ms/step
Epoch 604/1500
51/51 - 1s - loss: 0.0966 - categorical_accuracy: 0.9643 - val_loss: 1.5958 - val_categorical_accuracy: 0.8014 - 526ms/epoch - 10ms/step
Epoch 605/1500
51/51 - 1s - loss: 0.0976 - categorical_accuracy: 0.9644 - val_loss: 1.6551 - val_categorical_accuracy: 0.8077 - 506ms/epoch - 10ms/step
Epoch 606/1500
51/51 - 1s - loss: 0.0936 - categorical_accuracy: 0.9663 - val_loss: 1.7119 - val_categorical_accuracy: 0.8051 - 522ms/epoch - 10ms/step
Epoch 607/1500
51/51 - 1s - loss: 0.1100 - categorical_accuracy: 0.9595 - val_loss: 1.6420 - val_categorical_accuracy: 0.8052 - 526ms/epoch - 10ms/step
Epoch 608/1500
51/51 - 1s - loss: 0.0932 - categorical_accuracy: 0.9660 - val_loss: 1.5998 - val_categorical_accuracy: 0.7999 - 546ms/epoch - 11ms/step
Epoch 609/1500
51/51 - 1s - loss: 0.0933 - categorical_accuracy: 0.9658 - val_loss: 1.6223 - val_categorical_accuracy: 0.8022 - 516ms/epoch - 10ms/step
Epoch 610/1500
51/51 - 1s - loss: 0.1158 - categorical_accuracy: 0.9578 - val_loss: 1.6395 - val_categorical_accuracy: 0.7970 - 526ms/epoch - 10ms/step
Epoch 611/1500
51/51 - 0s - loss: 0.2296 - categorical_accuracy: 0.9293 - val_loss: 1.4917 - val_categorical_accuracy: 0.8013 - 493ms/epoch - 10ms/step
Epoch 612/1500
51/51 - 1s - loss: 0.1015 - categorical_accuracy: 0.9630 - val_loss: 1.5850 - val_categorical_accuracy: 0.8057 - 547ms/epoch - 11ms/step
Epoch 613/1500
51/51 - 1s - loss: 0.0983 - categorical_accuracy: 0.9651 - val_loss: 1.6160 - val_categorical_accuracy: 0.8036 - 503ms/epoch - 10ms/step
Epoch 614/1500
51/51 - 1s - loss: 0.0969 - categorical_accuracy: 0.9639 - val_loss: 1.6177 - val_categorical_accuracy: 0.8016 - 553ms/epoch - 11ms/step
Epoch 615/1500
51/51 - 1s - loss: 0.0948 - categorical_accuracy: 0.9656 - val_loss: 1.6330 - val_categorical_accuracy: 0.8012 - 520ms/epoch - 10ms/step
Epoch 616/1500
51/51 - 1s - loss: 0.0961 - categorical_accuracy: 0.9642 - val_loss: 1.6258 - val_categorical_accuracy: 0.8016 - 526ms/epoch - 10ms/step
Epoch 617/1500
51/51 - 1s - loss: 0.0942 - categorical_accuracy: 0.9651 - val_loss: 1.6191 - val_categorical_accuracy: 0.7986 - 528ms/epoch - 10ms/step
Epoch 618/1500
51/51 - 1s - loss: 0.0984 - categorical_accuracy: 0.9648 - val_loss: 1.6792 - val_categorical_accuracy: 0.7963 - 553ms/epoch - 11ms/step
Epoch 619/1500
51/51 - 1s - loss: 0.0989 - categorical_accuracy: 0.9645 - val_loss: 1.6502 - val_categorical_accuracy: 0.7952 - 532ms/epoch - 10ms/step
Epoch 620/1500
51/51 - 1s - loss: 0.0941 - categorical_accuracy: 0.9648 - val_loss: 1.6691 - val_categorical_accuracy: 0.7888 - 506ms/epoch - 10ms/step
Epoch 621/1500
51/51 - 1s - loss: 0.1038 - categorical_accuracy: 0.9615 - val_loss: 1.6631 - val_categorical_accuracy: 0.8005 - 543ms/epoch - 11ms/step
Epoch 622/1500
51/51 - 1s - loss: 0.0935 - categorical_accuracy: 0.9646 - val_loss: 1.6680 - val_categorical_accuracy: 0.7935 - 505ms/epoch - 10ms/step
Epoch 623/1500
51/51 - 1s - loss: 0.0966 - categorical_accuracy: 0.9645 - val_loss: 1.7344 - val_categorical_accuracy: 0.7958 - 581ms/epoch - 11ms/step
Epoch 624/1500
51/51 - 1s - loss: 0.1066 - categorical_accuracy: 0.9610 - val_loss: 1.8509 - val_categorical_accuracy: 0.7907 - 501ms/epoch - 10ms/step
Epoch 625/1500
51/51 - 1s - loss: 0.2567 - categorical_accuracy: 0.9197 - val_loss: 1.4947 - val_categorical_accuracy: 0.7908 - 532ms/epoch - 10ms/step
Epoch 626/1500
51/51 - 1s - loss: 0.1022 - categorical_accuracy: 0.9619 - val_loss: 1.6533 - val_categorical_accuracy: 0.8054 - 504ms/epoch - 10ms/step
Epoch 627/1500
51/51 - 1s - loss: 0.1013 - categorical_accuracy: 0.9630 - val_loss: 1.5820 - val_categorical_accuracy: 0.7872 - 545ms/epoch - 11ms/step
Epoch 628/1500
51/51 - 0s - loss: 0.1106 - categorical_accuracy: 0.9598 - val_loss: 1.5951 - val_categorical_accuracy: 0.8026 - 493ms/epoch - 10ms/step
Epoch 629/1500
51/51 - 1s - loss: 0.0917 - categorical_accuracy: 0.9662 - val_loss: 1.6089 - val_categorical_accuracy: 0.7989 - 533ms/epoch - 10ms/step
Epoch 630/1500
51/51 - 0s - loss: 0.0915 - categorical_accuracy: 0.9653 - val_loss: 1.7134 - val_categorical_accuracy: 0.8007 - 491ms/epoch - 10ms/step
Epoch 631/1500
51/51 - 1s - loss: 0.0986 - categorical_accuracy: 0.9636 - val_loss: 1.6702 - val_categorical_accuracy: 0.7814 - 541ms/epoch - 11ms/step
Epoch 632/1500
51/51 - 1s - loss: 0.1003 - categorical_accuracy: 0.9635 - val_loss: 1.6763 - val_categorical_accuracy: 0.7946 - 539ms/epoch - 11ms/step
Epoch 633/1500
51/51 - 1s - loss: 0.0963 - categorical_accuracy: 0.9637 - val_loss: 1.7140 - val_categorical_accuracy: 0.7982 - 603ms/epoch - 12ms/step
Epoch 634/1500
51/51 - 1s - loss: 0.2632 - categorical_accuracy: 0.9304 - val_loss: 1.3734 - val_categorical_accuracy: 0.7972 - 534ms/epoch - 10ms/step
Epoch 635/1500
51/51 - 1s - loss: 0.1130 - categorical_accuracy: 0.9589 - val_loss: 1.5562 - val_categorical_accuracy: 0.7812 - 571ms/epoch - 11ms/step
Epoch 636/1500
51/51 - 1s - loss: 0.1045 - categorical_accuracy: 0.9618 - val_loss: 1.5556 - val_categorical_accuracy: 0.7961 - 595ms/epoch - 12ms/step
Epoch 637/1500
51/51 - 1s - loss: 0.0917 - categorical_accuracy: 0.9664 - val_loss: 1.6202 - val_categorical_accuracy: 0.7954 - 549ms/epoch - 11ms/step
Epoch 638/1500
51/51 - 1s - loss: 0.0928 - categorical_accuracy: 0.9667 - val_loss: 1.6071 - val_categorical_accuracy: 0.8052 - 602ms/epoch - 12ms/step
Epoch 639/1500
51/51 - 1s - loss: 0.0930 - categorical_accuracy: 0.9653 - val_loss: 1.6063 - val_categorical_accuracy: 0.7935 - 529ms/epoch - 10ms/step
Epoch 640/1500
51/51 - 1s - loss: 0.0947 - categorical_accuracy: 0.9648 - val_loss: 1.6593 - val_categorical_accuracy: 0.7934 - 580ms/epoch - 11ms/step
Epoch 641/1500
51/51 - 1s - loss: 0.0895 - categorical_accuracy: 0.9665 - val_loss: 1.7173 - val_categorical_accuracy: 0.7980 - 547ms/epoch - 11ms/step
Epoch 642/1500
51/51 - 1s - loss: 0.1006 - categorical_accuracy: 0.9628 - val_loss: 1.6812 - val_categorical_accuracy: 0.8012 - 555ms/epoch - 11ms/step
Epoch 643/1500
51/51 - 1s - loss: 0.0921 - categorical_accuracy: 0.9658 - val_loss: 1.6926 - val_categorical_accuracy: 0.7999 - 571ms/epoch - 11ms/step
Epoch 644/1500
51/51 - 1s - loss: 0.0990 - categorical_accuracy: 0.9633 - val_loss: 1.6904 - val_categorical_accuracy: 0.7982 - 560ms/epoch - 11ms/step
Epoch 645/1500
51/51 - 1s - loss: 0.0984 - categorical_accuracy: 0.9640 - val_loss: 1.6995 - val_categorical_accuracy: 0.7972 - 571ms/epoch - 11ms/step
Epoch 646/1500
51/51 - 1s - loss: 0.1028 - categorical_accuracy: 0.9611 - val_loss: 1.7551 - val_categorical_accuracy: 0.7932 - 527ms/epoch - 10ms/step
Epoch 647/1500
51/51 - 1s - loss: 0.1038 - categorical_accuracy: 0.9619 - val_loss: 1.6691 - val_categorical_accuracy: 0.7959 - 584ms/epoch - 11ms/step
Epoch 648/1500
51/51 - 1s - loss: 0.1001 - categorical_accuracy: 0.9624 - val_loss: 1.7270 - val_categorical_accuracy: 0.7992 - 545ms/epoch - 11ms/step
Epoch 649/1500
51/51 - 1s - loss: 0.1088 - categorical_accuracy: 0.9602 - val_loss: 1.7675 - val_categorical_accuracy: 0.7823 - 575ms/epoch - 11ms/step
Epoch 650/1500
51/51 - 1s - loss: 0.1018 - categorical_accuracy: 0.9619 - val_loss: 1.6986 - val_categorical_accuracy: 0.8018 - 536ms/epoch - 11ms/step
Epoch 651/1500
51/51 - 1s - loss: 0.0906 - categorical_accuracy: 0.9666 - val_loss: 1.7211 - val_categorical_accuracy: 0.7937 - 567ms/epoch - 11ms/step
Epoch 652/1500
51/51 - 1s - loss: 0.1908 - categorical_accuracy: 0.9467 - val_loss: 1.7966 - val_categorical_accuracy: 0.6467 - 569ms/epoch - 11ms/step
Epoch 653/1500
51/51 - 1s - loss: 0.2084 - categorical_accuracy: 0.9317 - val_loss: 1.5479 - val_categorical_accuracy: 0.7995 - 556ms/epoch - 11ms/step
Epoch 654/1500
51/51 - 1s - loss: 0.0957 - categorical_accuracy: 0.9654 - val_loss: 1.5644 - val_categorical_accuracy: 0.8011 - 621ms/epoch - 12ms/step
Epoch 655/1500
51/51 - 1s - loss: 0.0887 - categorical_accuracy: 0.9675 - val_loss: 1.6291 - val_categorical_accuracy: 0.7988 - 557ms/epoch - 11ms/step
Epoch 656/1500
51/51 - 1s - loss: 0.0902 - categorical_accuracy: 0.9666 - val_loss: 1.6768 - val_categorical_accuracy: 0.8014 - 511ms/epoch - 10ms/step
Epoch 657/1500
51/51 - 1s - loss: 0.0952 - categorical_accuracy: 0.9647 - val_loss: 1.6896 - val_categorical_accuracy: 0.7899 - 510ms/epoch - 10ms/step
Epoch 658/1500
51/51 - 1s - loss: 0.0911 - categorical_accuracy: 0.9661 - val_loss: 1.7093 - val_categorical_accuracy: 0.7967 - 524ms/epoch - 10ms/step
Epoch 659/1500
51/51 - 1s - loss: 0.0908 - categorical_accuracy: 0.9658 - val_loss: 1.7069 - val_categorical_accuracy: 0.8025 - 526ms/epoch - 10ms/step
Epoch 660/1500
51/51 - 1s - loss: 0.0938 - categorical_accuracy: 0.9647 - val_loss: 1.6851 - val_categorical_accuracy: 0.7925 - 542ms/epoch - 11ms/step
Epoch 661/1500
51/51 - 1s - loss: 0.0928 - categorical_accuracy: 0.9661 - val_loss: 1.7110 - val_categorical_accuracy: 0.7949 - 536ms/epoch - 11ms/step
Epoch 662/1500
51/51 - 1s - loss: 0.0919 - categorical_accuracy: 0.9676 - val_loss: 1.7177 - val_categorical_accuracy: 0.8007 - 534ms/epoch - 10ms/step
Epoch 663/1500
51/51 - 1s - loss: 0.0871 - categorical_accuracy: 0.9677 - val_loss: 1.7346 - val_categorical_accuracy: 0.8032 - 531ms/epoch - 10ms/step
Epoch 664/1500
51/51 - 1s - loss: 0.0902 - categorical_accuracy: 0.9659 - val_loss: 1.7481 - val_categorical_accuracy: 0.7936 - 501ms/epoch - 10ms/step
Epoch 665/1500
51/51 - 1s - loss: 0.0891 - categorical_accuracy: 0.9670 - val_loss: 1.7111 - val_categorical_accuracy: 0.8005 - 526ms/epoch - 10ms/step
Epoch 666/1500
51/51 - 1s - loss: 0.0871 - categorical_accuracy: 0.9671 - val_loss: 1.7454 - val_categorical_accuracy: 0.7806 - 515ms/epoch - 10ms/step
Epoch 667/1500
51/51 - 1s - loss: 0.0972 - categorical_accuracy: 0.9637 - val_loss: 1.7356 - val_categorical_accuracy: 0.7898 - 537ms/epoch - 11ms/step
Epoch 668/1500
51/51 - 0s - loss: 0.0934 - categorical_accuracy: 0.9651 - val_loss: 1.7335 - val_categorical_accuracy: 0.8018 - 493ms/epoch - 10ms/step
Epoch 669/1500
51/51 - 1s - loss: 0.0893 - categorical_accuracy: 0.9660 - val_loss: 1.7463 - val_categorical_accuracy: 0.7868 - 539ms/epoch - 11ms/step
Epoch 670/1500
51/51 - 1s - loss: 0.0921 - categorical_accuracy: 0.9654 - val_loss: 1.8451 - val_categorical_accuracy: 0.8005 - 505ms/epoch - 10ms/step
Epoch 671/1500
51/51 - 1s - loss: 0.3572 - categorical_accuracy: 0.9089 - val_loss: 1.3711 - val_categorical_accuracy: 0.7896 - 541ms/epoch - 11ms/step
Epoch 672/1500
51/51 - 0s - loss: 0.1191 - categorical_accuracy: 0.9562 - val_loss: 1.6164 - val_categorical_accuracy: 0.8014 - 492ms/epoch - 10ms/step
Epoch 673/1500
51/51 - 1s - loss: 0.1010 - categorical_accuracy: 0.9622 - val_loss: 1.6403 - val_categorical_accuracy: 0.8039 - 571ms/epoch - 11ms/step
Epoch 674/1500
51/51 - 1s - loss: 0.1245 - categorical_accuracy: 0.9541 - val_loss: 1.6140 - val_categorical_accuracy: 0.7993 - 508ms/epoch - 10ms/step
Epoch 675/1500
51/51 - 1s - loss: 0.0914 - categorical_accuracy: 0.9665 - val_loss: 1.6307 - val_categorical_accuracy: 0.8025 - 527ms/epoch - 10ms/step
Epoch 676/1500
51/51 - 1s - loss: 0.0866 - categorical_accuracy: 0.9680 - val_loss: 1.6804 - val_categorical_accuracy: 0.7949 - 507ms/epoch - 10ms/step
Epoch 677/1500
51/51 - 1s - loss: 0.0907 - categorical_accuracy: 0.9666 - val_loss: 1.6817 - val_categorical_accuracy: 0.7989 - 521ms/epoch - 10ms/step
Epoch 678/1500
51/51 - 1s - loss: 0.0876 - categorical_accuracy: 0.9670 - val_loss: 1.6962 - val_categorical_accuracy: 0.7928 - 525ms/epoch - 10ms/step
Epoch 679/1500
51/51 - 1s - loss: 0.0945 - categorical_accuracy: 0.9656 - val_loss: 1.6960 - val_categorical_accuracy: 0.7989 - 515ms/epoch - 10ms/step
Epoch 680/1500
51/51 - 1s - loss: 0.0965 - categorical_accuracy: 0.9648 - val_loss: 1.6538 - val_categorical_accuracy: 0.7846 - 520ms/epoch - 10ms/step
Epoch 681/1500
51/51 - 1s - loss: 0.0904 - categorical_accuracy: 0.9659 - val_loss: 1.6899 - val_categorical_accuracy: 0.8025 - 519ms/epoch - 10ms/step
Epoch 682/1500
51/51 - 1s - loss: 0.0885 - categorical_accuracy: 0.9667 - val_loss: 1.7004 - val_categorical_accuracy: 0.7994 - 520ms/epoch - 10ms/step
Epoch 683/1500
51/51 - 1s - loss: 0.0921 - categorical_accuracy: 0.9659 - val_loss: 1.7431 - val_categorical_accuracy: 0.8004 - 520ms/epoch - 10ms/step
Epoch 684/1500
51/51 - 1s - loss: 0.0843 - categorical_accuracy: 0.9683 - val_loss: 1.7240 - val_categorical_accuracy: 0.7941 - 519ms/epoch - 10ms/step
Epoch 685/1500
51/51 - 1s - loss: 0.0871 - categorical_accuracy: 0.9684 - val_loss: 1.8336 - val_categorical_accuracy: 0.7802 - 504ms/epoch - 10ms/step
Epoch 686/1500
51/51 - 1s - loss: 0.0971 - categorical_accuracy: 0.9643 - val_loss: 1.7205 - val_categorical_accuracy: 0.7991 - 526ms/epoch - 10ms/step
Epoch 687/1500
51/51 - 0s - loss: 0.0902 - categorical_accuracy: 0.9661 - val_loss: 1.7756 - val_categorical_accuracy: 0.8067 - 494ms/epoch - 10ms/step
Epoch 688/1500
51/51 - 1s - loss: 0.0949 - categorical_accuracy: 0.9640 - val_loss: 1.7292 - val_categorical_accuracy: 0.7963 - 524ms/epoch - 10ms/step
Epoch 689/1500
51/51 - 0s - loss: 0.0822 - categorical_accuracy: 0.9694 - val_loss: 1.7806 - val_categorical_accuracy: 0.8009 - 487ms/epoch - 10ms/step
Epoch 690/1500
51/51 - 1s - loss: 0.1059 - categorical_accuracy: 0.9611 - val_loss: 1.8191 - val_categorical_accuracy: 0.8027 - 535ms/epoch - 10ms/step
Epoch 691/1500
51/51 - 0s - loss: 0.0993 - categorical_accuracy: 0.9627 - val_loss: 1.7273 - val_categorical_accuracy: 0.7880 - 495ms/epoch - 10ms/step
Epoch 692/1500
51/51 - 1s - loss: 0.3541 - categorical_accuracy: 0.9116 - val_loss: 1.3838 - val_categorical_accuracy: 0.7862 - 556ms/epoch - 11ms/step
Epoch 693/1500
51/51 - 0s - loss: 0.1132 - categorical_accuracy: 0.9583 - val_loss: 1.5574 - val_categorical_accuracy: 0.8009 - 493ms/epoch - 10ms/step
Epoch 694/1500
51/51 - 1s - loss: 0.0902 - categorical_accuracy: 0.9668 - val_loss: 1.6906 - val_categorical_accuracy: 0.8086 - 542ms/epoch - 11ms/step
Epoch 695/1500
51/51 - 0s - loss: 0.0861 - categorical_accuracy: 0.9683 - val_loss: 1.6744 - val_categorical_accuracy: 0.8063 - 494ms/epoch - 10ms/step
Epoch 696/1500
51/51 - 1s - loss: 0.0889 - categorical_accuracy: 0.9673 - val_loss: 1.6894 - val_categorical_accuracy: 0.7975 - 547ms/epoch - 11ms/step
Epoch 697/1500
51/51 - 0s - loss: 0.0881 - categorical_accuracy: 0.9677 - val_loss: 1.7054 - val_categorical_accuracy: 0.8009 - 477ms/epoch - 9ms/step
Epoch 698/1500
51/51 - 1s - loss: 0.0887 - categorical_accuracy: 0.9677 - val_loss: 1.7132 - val_categorical_accuracy: 0.8050 - 544ms/epoch - 11ms/step
Epoch 699/1500
51/51 - 0s - loss: 0.0835 - categorical_accuracy: 0.9685 - val_loss: 1.7174 - val_categorical_accuracy: 0.7945 - 490ms/epoch - 10ms/step
Epoch 700/1500
51/51 - 1s - loss: 0.0883 - categorical_accuracy: 0.9662 - val_loss: 1.7708 - val_categorical_accuracy: 0.8002 - 521ms/epoch - 10ms/step
Epoch 701/1500
51/51 - 0s - loss: 0.1012 - categorical_accuracy: 0.9614 - val_loss: 1.7494 - val_categorical_accuracy: 0.8029 - 484ms/epoch - 9ms/step
Epoch 702/1500
51/51 - 1s - loss: 0.0974 - categorical_accuracy: 0.9644 - val_loss: 1.8116 - val_categorical_accuracy: 0.7781 - 522ms/epoch - 10ms/step
Epoch 703/1500
51/51 - 0s - loss: 0.0976 - categorical_accuracy: 0.9640 - val_loss: 1.7928 - val_categorical_accuracy: 0.7805 - 492ms/epoch - 10ms/step
Epoch 704/1500
51/51 - 1s - loss: 0.1010 - categorical_accuracy: 0.9626 - val_loss: 1.7912 - val_categorical_accuracy: 0.8010 - 522ms/epoch - 10ms/step
Epoch 705/1500
51/51 - 0s - loss: 0.0890 - categorical_accuracy: 0.9677 - val_loss: 1.7881 - val_categorical_accuracy: 0.8002 - 495ms/epoch - 10ms/step
Epoch 706/1500
51/51 - 1s - loss: 0.0895 - categorical_accuracy: 0.9665 - val_loss: 1.7684 - val_categorical_accuracy: 0.7988 - 510ms/epoch - 10ms/step
Epoch 707/1500
51/51 - 0s - loss: 0.2765 - categorical_accuracy: 0.9244 - val_loss: 1.3973 - val_categorical_accuracy: 0.7798 - 494ms/epoch - 10ms/step
Epoch 708/1500
51/51 - 1s - loss: 0.1105 - categorical_accuracy: 0.9596 - val_loss: 1.5724 - val_categorical_accuracy: 0.7969 - 526ms/epoch - 10ms/step
Epoch 709/1500
51/51 - 0s - loss: 0.0860 - categorical_accuracy: 0.9699 - val_loss: 1.6542 - val_categorical_accuracy: 0.8007 - 489ms/epoch - 10ms/step
Epoch 710/1500
51/51 - 1s - loss: 0.0846 - categorical_accuracy: 0.9680 - val_loss: 1.7259 - val_categorical_accuracy: 0.8061 - 523ms/epoch - 10ms/step
Epoch 711/1500
51/51 - 1s - loss: 0.0826 - categorical_accuracy: 0.9699 - val_loss: 1.7099 - val_categorical_accuracy: 0.7983 - 504ms/epoch - 10ms/step
Epoch 712/1500
51/51 - 1s - loss: 0.0810 - categorical_accuracy: 0.9712 - val_loss: 1.7770 - val_categorical_accuracy: 0.7976 - 548ms/epoch - 11ms/step
Epoch 713/1500
51/51 - 1s - loss: 0.0832 - categorical_accuracy: 0.9695 - val_loss: 1.7703 - val_categorical_accuracy: 0.8052 - 507ms/epoch - 10ms/step
Epoch 714/1500
51/51 - 1s - loss: 0.0883 - categorical_accuracy: 0.9666 - val_loss: 1.7184 - val_categorical_accuracy: 0.7955 - 527ms/epoch - 10ms/step
Epoch 715/1500
51/51 - 1s - loss: 0.0935 - categorical_accuracy: 0.9646 - val_loss: 1.7412 - val_categorical_accuracy: 0.7957 - 522ms/epoch - 10ms/step
Epoch 716/1500
51/51 - 1s - loss: 0.0864 - categorical_accuracy: 0.9679 - val_loss: 1.7985 - val_categorical_accuracy: 0.7980 - 513ms/epoch - 10ms/step
Epoch 717/1500
51/51 - 1s - loss: 0.0902 - categorical_accuracy: 0.9667 - val_loss: 1.7946 - val_categorical_accuracy: 0.7974 - 521ms/epoch - 10ms/step
Epoch 718/1500
51/51 - 1s - loss: 0.0892 - categorical_accuracy: 0.9670 - val_loss: 1.7889 - val_categorical_accuracy: 0.8000 - 523ms/epoch - 10ms/step
Epoch 719/1500
51/51 - 1s - loss: 0.1847 - categorical_accuracy: 0.9419 - val_loss: 1.6984 - val_categorical_accuracy: 0.7900 - 521ms/epoch - 10ms/step
Epoch 720/1500
51/51 - 1s - loss: 0.1141 - categorical_accuracy: 0.9587 - val_loss: 1.6927 - val_categorical_accuracy: 0.8010 - 503ms/epoch - 10ms/step
Epoch 721/1500
51/51 - 1s - loss: 0.0865 - categorical_accuracy: 0.9677 - val_loss: 1.7282 - val_categorical_accuracy: 0.8040 - 524ms/epoch - 10ms/step
Epoch 722/1500
51/51 - 0s - loss: 0.0889 - categorical_accuracy: 0.9670 - val_loss: 1.7286 - val_categorical_accuracy: 0.8008 - 496ms/epoch - 10ms/step
Epoch 723/1500
51/51 - 1s - loss: 0.0965 - categorical_accuracy: 0.9664 - val_loss: 1.7499 - val_categorical_accuracy: 0.8020 - 554ms/epoch - 11ms/step
Epoch 724/1500
51/51 - 1s - loss: 0.0848 - categorical_accuracy: 0.9685 - val_loss: 1.7845 - val_categorical_accuracy: 0.7994 - 505ms/epoch - 10ms/step
Epoch 725/1500
51/51 - 1s - loss: 0.0826 - categorical_accuracy: 0.9691 - val_loss: 1.8132 - val_categorical_accuracy: 0.7918 - 521ms/epoch - 10ms/step
Epoch 726/1500
51/51 - 0s - loss: 0.0855 - categorical_accuracy: 0.9679 - val_loss: 1.8540 - val_categorical_accuracy: 0.7760 - 482ms/epoch - 9ms/step
Epoch 727/1500
51/51 - 1s - loss: 0.0932 - categorical_accuracy: 0.9660 - val_loss: 1.7941 - val_categorical_accuracy: 0.7898 - 536ms/epoch - 11ms/step
Epoch 728/1500
51/51 - 1s - loss: 0.0823 - categorical_accuracy: 0.9694 - val_loss: 1.8331 - val_categorical_accuracy: 0.8005 - 513ms/epoch - 10ms/step
Epoch 729/1500
51/51 - 1s - loss: 0.6625 - categorical_accuracy: 0.8355 - val_loss: 1.1994 - val_categorical_accuracy: 0.8000 - 534ms/epoch - 10ms/step
Epoch 730/1500
51/51 - 0s - loss: 0.1454 - categorical_accuracy: 0.9467 - val_loss: 1.3768 - val_categorical_accuracy: 0.7968 - 488ms/epoch - 10ms/step
Epoch 731/1500
51/51 - 1s - loss: 0.0947 - categorical_accuracy: 0.9661 - val_loss: 1.5348 - val_categorical_accuracy: 0.8013 - 548ms/epoch - 11ms/step
Epoch 732/1500
51/51 - 0s - loss: 0.0877 - categorical_accuracy: 0.9681 - val_loss: 1.5445 - val_categorical_accuracy: 0.8027 - 490ms/epoch - 10ms/step
Epoch 733/1500
51/51 - 1s - loss: 0.0845 - categorical_accuracy: 0.9678 - val_loss: 1.6575 - val_categorical_accuracy: 0.7975 - 554ms/epoch - 11ms/step
Epoch 734/1500
51/51 - 1s - loss: 0.0849 - categorical_accuracy: 0.9686 - val_loss: 1.6375 - val_categorical_accuracy: 0.7933 - 506ms/epoch - 10ms/step
Epoch 735/1500
51/51 - 1s - loss: 0.0850 - categorical_accuracy: 0.9690 - val_loss: 1.6602 - val_categorical_accuracy: 0.7962 - 524ms/epoch - 10ms/step
Epoch 736/1500
51/51 - 1s - loss: 0.0825 - categorical_accuracy: 0.9693 - val_loss: 1.7088 - val_categorical_accuracy: 0.8043 - 509ms/epoch - 10ms/step
Epoch 737/1500
51/51 - 1s - loss: 0.0822 - categorical_accuracy: 0.9690 - val_loss: 1.7407 - val_categorical_accuracy: 0.7982 - 508ms/epoch - 10ms/step
Epoch 738/1500
51/51 - 0s - loss: 0.0816 - categorical_accuracy: 0.9692 - val_loss: 1.7345 - val_categorical_accuracy: 0.8018 - 500ms/epoch - 10ms/step
Epoch 739/1500
51/51 - 1s - loss: 0.0907 - categorical_accuracy: 0.9677 - val_loss: 1.8233 - val_categorical_accuracy: 0.8045 - 525ms/epoch - 10ms/step
Epoch 740/1500
51/51 - 1s - loss: 0.0891 - categorical_accuracy: 0.9672 - val_loss: 1.7153 - val_categorical_accuracy: 0.7921 - 524ms/epoch - 10ms/step
Epoch 741/1500
51/51 - 0s - loss: 0.0894 - categorical_accuracy: 0.9661 - val_loss: 1.7257 - val_categorical_accuracy: 0.7927 - 494ms/epoch - 10ms/step
Epoch 742/1500
51/51 - 1s - loss: 0.0806 - categorical_accuracy: 0.9702 - val_loss: 1.8048 - val_categorical_accuracy: 0.7945 - 525ms/epoch - 10ms/step
Epoch 743/1500
51/51 - 1s - loss: 0.0845 - categorical_accuracy: 0.9683 - val_loss: 1.8425 - val_categorical_accuracy: 0.8052 - 515ms/epoch - 10ms/step
Epoch 744/1500
51/51 - 1s - loss: 0.0876 - categorical_accuracy: 0.9671 - val_loss: 1.7455 - val_categorical_accuracy: 0.7949 - 523ms/epoch - 10ms/step
Epoch 745/1500
51/51 - 0s - loss: 0.0834 - categorical_accuracy: 0.9679 - val_loss: 1.8321 - val_categorical_accuracy: 0.8034 - 494ms/epoch - 10ms/step
Epoch 746/1500
51/51 - 1s - loss: 0.0845 - categorical_accuracy: 0.9682 - val_loss: 1.7832 - val_categorical_accuracy: 0.7992 - 513ms/epoch - 10ms/step
Epoch 747/1500
51/51 - 0s - loss: 0.0818 - categorical_accuracy: 0.9697 - val_loss: 1.8248 - val_categorical_accuracy: 0.7959 - 490ms/epoch - 10ms/step
Epoch 748/1500
51/51 - 1s - loss: 0.0838 - categorical_accuracy: 0.9688 - val_loss: 1.8421 - val_categorical_accuracy: 0.7996 - 538ms/epoch - 11ms/step
Epoch 749/1500
51/51 - 0s - loss: 0.0798 - categorical_accuracy: 0.9704 - val_loss: 1.8523 - val_categorical_accuracy: 0.7891 - 496ms/epoch - 10ms/step
Epoch 750/1500
51/51 - 1s - loss: 0.0828 - categorical_accuracy: 0.9694 - val_loss: 1.8366 - val_categorical_accuracy: 0.7995 - 562ms/epoch - 11ms/step
Epoch 751/1500
51/51 - 0s - loss: 0.3549 - categorical_accuracy: 0.9103 - val_loss: 1.3771 - val_categorical_accuracy: 0.7904 - 488ms/epoch - 10ms/step
Epoch 752/1500
51/51 - 1s - loss: 0.1094 - categorical_accuracy: 0.9593 - val_loss: 1.6511 - val_categorical_accuracy: 0.7908 - 534ms/epoch - 10ms/step
Epoch 753/1500
51/51 - 0s - loss: 0.0879 - categorical_accuracy: 0.9681 - val_loss: 1.6981 - val_categorical_accuracy: 0.8006 - 490ms/epoch - 10ms/step
Epoch 754/1500
51/51 - 1s - loss: 0.0832 - categorical_accuracy: 0.9692 - val_loss: 1.7271 - val_categorical_accuracy: 0.7991 - 534ms/epoch - 10ms/step
Epoch 755/1500
51/51 - 0s - loss: 0.0846 - categorical_accuracy: 0.9689 - val_loss: 1.7603 - val_categorical_accuracy: 0.7859 - 489ms/epoch - 10ms/step
Epoch 756/1500
51/51 - 1s - loss: 0.0888 - categorical_accuracy: 0.9669 - val_loss: 1.7923 - val_categorical_accuracy: 0.7957 - 521ms/epoch - 10ms/step
Epoch 757/1500
51/51 - 0s - loss: 0.0821 - categorical_accuracy: 0.9684 - val_loss: 1.7385 - val_categorical_accuracy: 0.7991 - 474ms/epoch - 9ms/step
Epoch 758/1500
51/51 - 1s - loss: 0.0828 - categorical_accuracy: 0.9682 - val_loss: 1.8057 - val_categorical_accuracy: 0.7938 - 535ms/epoch - 10ms/step
Epoch 759/1500
51/51 - 1s - loss: 0.2715 - categorical_accuracy: 0.9151 - val_loss: 1.5187 - val_categorical_accuracy: 0.7883 - 509ms/epoch - 10ms/step
Epoch 760/1500
51/51 - 1s - loss: 0.0970 - categorical_accuracy: 0.9645 - val_loss: 1.6374 - val_categorical_accuracy: 0.7961 - 566ms/epoch - 11ms/step
Epoch 761/1500
51/51 - 1s - loss: 0.0875 - categorical_accuracy: 0.9669 - val_loss: 1.6947 - val_categorical_accuracy: 0.8032 - 541ms/epoch - 11ms/step
Epoch 762/1500
51/51 - 1s - loss: 0.0838 - categorical_accuracy: 0.9685 - val_loss: 1.7111 - val_categorical_accuracy: 0.7958 - 559ms/epoch - 11ms/step
Epoch 763/1500
51/51 - 1s - loss: 0.0887 - categorical_accuracy: 0.9668 - val_loss: 1.7312 - val_categorical_accuracy: 0.7860 - 524ms/epoch - 10ms/step
Epoch 764/1500
51/51 - 1s - loss: 0.0865 - categorical_accuracy: 0.9677 - val_loss: 1.8082 - val_categorical_accuracy: 0.8015 - 557ms/epoch - 11ms/step
Epoch 765/1500
51/51 - 1s - loss: 0.0855 - categorical_accuracy: 0.9692 - val_loss: 1.7628 - val_categorical_accuracy: 0.7947 - 563ms/epoch - 11ms/step
Epoch 766/1500
51/51 - 1s - loss: 0.0807 - categorical_accuracy: 0.9704 - val_loss: 1.7588 - val_categorical_accuracy: 0.7954 - 548ms/epoch - 11ms/step
Epoch 767/1500
51/51 - 1s - loss: 0.0759 - categorical_accuracy: 0.9714 - val_loss: 1.8140 - val_categorical_accuracy: 0.7957 - 568ms/epoch - 11ms/step
Epoch 768/1500
51/51 - 1s - loss: 0.0861 - categorical_accuracy: 0.9687 - val_loss: 1.8300 - val_categorical_accuracy: 0.7959 - 525ms/epoch - 10ms/step
Epoch 769/1500
51/51 - 1s - loss: 0.2610 - categorical_accuracy: 0.9293 - val_loss: 1.5809 - val_categorical_accuracy: 0.8008 - 579ms/epoch - 11ms/step
Epoch 770/1500
51/51 - 1s - loss: 0.0898 - categorical_accuracy: 0.9671 - val_loss: 1.7269 - val_categorical_accuracy: 0.8013 - 542ms/epoch - 11ms/step
Epoch 771/1500
51/51 - 1s - loss: 0.0809 - categorical_accuracy: 0.9700 - val_loss: 1.7466 - val_categorical_accuracy: 0.8040 - 558ms/epoch - 11ms/step
Epoch 772/1500
51/51 - 1s - loss: 0.0857 - categorical_accuracy: 0.9682 - val_loss: 1.7372 - val_categorical_accuracy: 0.8001 - 556ms/epoch - 11ms/step
Epoch 773/1500
51/51 - 1s - loss: 0.0777 - categorical_accuracy: 0.9714 - val_loss: 1.7790 - val_categorical_accuracy: 0.8037 - 554ms/epoch - 11ms/step
Epoch 774/1500
51/51 - 1s - loss: 0.0784 - categorical_accuracy: 0.9708 - val_loss: 1.8063 - val_categorical_accuracy: 0.7982 - 559ms/epoch - 11ms/step
Epoch 775/1500
51/51 - 1s - loss: 0.0772 - categorical_accuracy: 0.9710 - val_loss: 1.7683 - val_categorical_accuracy: 0.8025 - 571ms/epoch - 11ms/step
Epoch 776/1500
51/51 - 1s - loss: 0.0841 - categorical_accuracy: 0.9687 - val_loss: 1.7812 - val_categorical_accuracy: 0.7970 - 590ms/epoch - 12ms/step
Epoch 777/1500
51/51 - 1s - loss: 0.0792 - categorical_accuracy: 0.9707 - val_loss: 1.8088 - val_categorical_accuracy: 0.7993 - 537ms/epoch - 11ms/step
Epoch 778/1500
51/51 - 1s - loss: 0.0785 - categorical_accuracy: 0.9702 - val_loss: 1.8466 - val_categorical_accuracy: 0.7947 - 590ms/epoch - 12ms/step
Epoch 779/1500
51/51 - 1s - loss: 0.0812 - categorical_accuracy: 0.9700 - val_loss: 1.8671 - val_categorical_accuracy: 0.7969 - 550ms/epoch - 11ms/step
Epoch 780/1500
51/51 - 1s - loss: 0.0863 - categorical_accuracy: 0.9669 - val_loss: 1.8738 - val_categorical_accuracy: 0.8063 - 544ms/epoch - 11ms/step
Epoch 781/1500
51/51 - 1s - loss: 0.2976 - categorical_accuracy: 0.9302 - val_loss: 1.1869 - val_categorical_accuracy: 0.7624 - 567ms/epoch - 11ms/step
Epoch 782/1500
51/51 - 1s - loss: 0.1701 - categorical_accuracy: 0.9370 - val_loss: 1.5765 - val_categorical_accuracy: 0.7956 - 538ms/epoch - 11ms/step
Epoch 783/1500
51/51 - 1s - loss: 0.0937 - categorical_accuracy: 0.9640 - val_loss: 1.6661 - val_categorical_accuracy: 0.7933 - 541ms/epoch - 11ms/step
Epoch 784/1500
51/51 - 1s - loss: 0.0843 - categorical_accuracy: 0.9694 - val_loss: 1.6871 - val_categorical_accuracy: 0.8050 - 509ms/epoch - 10ms/step
Epoch 785/1500
51/51 - 1s - loss: 0.0783 - categorical_accuracy: 0.9718 - val_loss: 1.7131 - val_categorical_accuracy: 0.8033 - 531ms/epoch - 10ms/step
Epoch 786/1500
51/51 - 0s - loss: 0.0779 - categorical_accuracy: 0.9707 - val_loss: 1.8019 - val_categorical_accuracy: 0.7738 - 475ms/epoch - 9ms/step
Epoch 787/1500
51/51 - 1s - loss: 0.0894 - categorical_accuracy: 0.9669 - val_loss: 1.7552 - val_categorical_accuracy: 0.8017 - 575ms/epoch - 11ms/step
Epoch 788/1500
51/51 - 0s - loss: 0.0796 - categorical_accuracy: 0.9713 - val_loss: 1.7924 - val_categorical_accuracy: 0.7974 - 491ms/epoch - 10ms/step
Epoch 789/1500
51/51 - 1s - loss: 0.0774 - categorical_accuracy: 0.9714 - val_loss: 1.7888 - val_categorical_accuracy: 0.7962 - 516ms/epoch - 10ms/step
Epoch 790/1500
51/51 - 0s - loss: 0.0765 - categorical_accuracy: 0.9713 - val_loss: 1.8154 - val_categorical_accuracy: 0.8016 - 484ms/epoch - 9ms/step
Epoch 791/1500
51/51 - 1s - loss: 0.0783 - categorical_accuracy: 0.9699 - val_loss: 1.8080 - val_categorical_accuracy: 0.7924 - 529ms/epoch - 10ms/step
Epoch 792/1500
51/51 - 0s - loss: 0.0796 - categorical_accuracy: 0.9699 - val_loss: 1.8222 - val_categorical_accuracy: 0.7986 - 475ms/epoch - 9ms/step
Epoch 793/1500
51/51 - 1s - loss: 0.0765 - categorical_accuracy: 0.9705 - val_loss: 1.9146 - val_categorical_accuracy: 0.7927 - 550ms/epoch - 11ms/step
Epoch 794/1500
51/51 - 1s - loss: 0.0773 - categorical_accuracy: 0.9716 - val_loss: 1.8441 - val_categorical_accuracy: 0.7989 - 500ms/epoch - 10ms/step
Epoch 795/1500
51/51 - 1s - loss: 0.0784 - categorical_accuracy: 0.9700 - val_loss: 1.8940 - val_categorical_accuracy: 0.7933 - 518ms/epoch - 10ms/step
Epoch 796/1500
51/51 - 0s - loss: 0.0943 - categorical_accuracy: 0.9646 - val_loss: 1.8449 - val_categorical_accuracy: 0.7911 - 483ms/epoch - 9ms/step
Epoch 797/1500
51/51 - 1s - loss: 0.0892 - categorical_accuracy: 0.9672 - val_loss: 1.8530 - val_categorical_accuracy: 0.7974 - 514ms/epoch - 10ms/step
Epoch 798/1500
51/51 - 0s - loss: 0.0857 - categorical_accuracy: 0.9690 - val_loss: 1.8640 - val_categorical_accuracy: 0.7954 - 490ms/epoch - 10ms/step
Epoch 799/1500
51/51 - 1s - loss: 0.0837 - categorical_accuracy: 0.9687 - val_loss: 1.8591 - val_categorical_accuracy: 0.7956 - 524ms/epoch - 10ms/step
Epoch 800/1500
51/51 - 0s - loss: 0.0818 - categorical_accuracy: 0.9687 - val_loss: 1.8650 - val_categorical_accuracy: 0.7895 - 491ms/epoch - 10ms/step
Epoch 801/1500
51/51 - 1s - loss: 0.0820 - categorical_accuracy: 0.9688 - val_loss: 1.8658 - val_categorical_accuracy: 0.7973 - 526ms/epoch - 10ms/step
Epoch 802/1500
51/51 - 0s - loss: 0.0798 - categorical_accuracy: 0.9704 - val_loss: 1.9343 - val_categorical_accuracy: 0.7970 - 492ms/epoch - 10ms/step
Epoch 803/1500
51/51 - 1s - loss: 0.0874 - categorical_accuracy: 0.9678 - val_loss: 1.9049 - val_categorical_accuracy: 0.7912 - 523ms/epoch - 10ms/step
Epoch 804/1500
51/51 - 0s - loss: 0.0796 - categorical_accuracy: 0.9703 - val_loss: 1.9061 - val_categorical_accuracy: 0.8006 - 477ms/epoch - 9ms/step
Epoch 805/1500
51/51 - 1s - loss: 0.0837 - categorical_accuracy: 0.9680 - val_loss: 1.8639 - val_categorical_accuracy: 0.7923 - 536ms/epoch - 11ms/step
Epoch 806/1500
51/51 - 1s - loss: 0.0795 - categorical_accuracy: 0.9703 - val_loss: 1.9462 - val_categorical_accuracy: 0.7871 - 500ms/epoch - 10ms/step
Epoch 807/1500
51/51 - 1s - loss: 0.3551 - categorical_accuracy: 0.9176 - val_loss: 1.1802 - val_categorical_accuracy: 0.7744 - 524ms/epoch - 10ms/step
Epoch 808/1500
51/51 - 1s - loss: 0.1564 - categorical_accuracy: 0.9425 - val_loss: 1.5401 - val_categorical_accuracy: 0.7986 - 520ms/epoch - 10ms/step
Epoch 809/1500
51/51 - 1s - loss: 0.0884 - categorical_accuracy: 0.9677 - val_loss: 1.6490 - val_categorical_accuracy: 0.8024 - 513ms/epoch - 10ms/step
Epoch 810/1500
51/51 - 0s - loss: 0.0793 - categorical_accuracy: 0.9712 - val_loss: 1.7548 - val_categorical_accuracy: 0.8042 - 500ms/epoch - 10ms/step
Epoch 811/1500
51/51 - 1s - loss: 0.0822 - categorical_accuracy: 0.9697 - val_loss: 1.7594 - val_categorical_accuracy: 0.7930 - 510ms/epoch - 10ms/step
Epoch 812/1500
51/51 - 1s - loss: 0.0794 - categorical_accuracy: 0.9701 - val_loss: 1.7816 - val_categorical_accuracy: 0.7969 - 500ms/epoch - 10ms/step
Epoch 813/1500
51/51 - 1s - loss: 0.0776 - categorical_accuracy: 0.9717 - val_loss: 1.8022 - val_categorical_accuracy: 0.8000 - 522ms/epoch - 10ms/step
Epoch 814/1500
51/51 - 1s - loss: 0.0763 - categorical_accuracy: 0.9714 - val_loss: 1.8166 - val_categorical_accuracy: 0.7920 - 511ms/epoch - 10ms/step
Epoch 815/1500
51/51 - 1s - loss: 0.0757 - categorical_accuracy: 0.9710 - val_loss: 1.8421 - val_categorical_accuracy: 0.7961 - 504ms/epoch - 10ms/step
Epoch 816/1500
51/51 - 0s - loss: 0.0800 - categorical_accuracy: 0.9708 - val_loss: 1.8079 - val_categorical_accuracy: 0.7933 - 496ms/epoch - 10ms/step
Epoch 817/1500
51/51 - 1s - loss: 0.0793 - categorical_accuracy: 0.9700 - val_loss: 1.8212 - val_categorical_accuracy: 0.7947 - 516ms/epoch - 10ms/step
Epoch 818/1500
51/51 - 1s - loss: 0.0822 - categorical_accuracy: 0.9692 - val_loss: 1.8268 - val_categorical_accuracy: 0.7962 - 531ms/epoch - 10ms/step
Epoch 819/1500
51/51 - 1s - loss: 0.0775 - categorical_accuracy: 0.9708 - val_loss: 1.8714 - val_categorical_accuracy: 0.8034 - 505ms/epoch - 10ms/step
Epoch 820/1500
51/51 - 1s - loss: 0.1090 - categorical_accuracy: 0.9626 - val_loss: 3.7558 - val_categorical_accuracy: 0.7603 - 506ms/epoch - 10ms/step
Epoch 821/1500
51/51 - 1s - loss: 0.2428 - categorical_accuracy: 0.9314 - val_loss: 1.7040 - val_categorical_accuracy: 0.8019 - 504ms/epoch - 10ms/step
Epoch 822/1500
51/51 - 1s - loss: 0.0867 - categorical_accuracy: 0.9681 - val_loss: 1.7303 - val_categorical_accuracy: 0.7951 - 506ms/epoch - 10ms/step
Epoch 823/1500
51/51 - 0s - loss: 0.0843 - categorical_accuracy: 0.9681 - val_loss: 1.7852 - val_categorical_accuracy: 0.7957 - 494ms/epoch - 10ms/step
Epoch 824/1500
51/51 - 1s - loss: 0.0853 - categorical_accuracy: 0.9680 - val_loss: 1.7953 - val_categorical_accuracy: 0.7928 - 525ms/epoch - 10ms/step
Epoch 825/1500
51/51 - 0s - loss: 0.0818 - categorical_accuracy: 0.9706 - val_loss: 1.8306 - val_categorical_accuracy: 0.7966 - 497ms/epoch - 10ms/step
Epoch 826/1500
51/51 - 1s - loss: 0.1027 - categorical_accuracy: 0.9635 - val_loss: 1.8431 - val_categorical_accuracy: 0.8012 - 563ms/epoch - 11ms/step
Epoch 827/1500
51/51 - 0s - loss: 0.0810 - categorical_accuracy: 0.9706 - val_loss: 1.8263 - val_categorical_accuracy: 0.7990 - 493ms/epoch - 10ms/step
Epoch 828/1500
51/51 - 1s - loss: 0.0831 - categorical_accuracy: 0.9687 - val_loss: 1.8318 - val_categorical_accuracy: 0.7934 - 520ms/epoch - 10ms/step
Epoch 829/1500
51/51 - 0s - loss: 0.0811 - categorical_accuracy: 0.9695 - val_loss: 1.8335 - val_categorical_accuracy: 0.7961 - 484ms/epoch - 9ms/step
Epoch 830/1500
51/51 - 1s - loss: 0.0750 - categorical_accuracy: 0.9723 - val_loss: 1.8530 - val_categorical_accuracy: 0.7987 - 527ms/epoch - 10ms/step
Epoch 831/1500
51/51 - 0s - loss: 0.0762 - categorical_accuracy: 0.9709 - val_loss: 1.9183 - val_categorical_accuracy: 0.7987 - 486ms/epoch - 10ms/step
Epoch 832/1500
51/51 - 1s - loss: 0.0758 - categorical_accuracy: 0.9709 - val_loss: 1.9067 - val_categorical_accuracy: 0.7962 - 517ms/epoch - 10ms/step
Epoch 833/1500
51/51 - 0s - loss: 0.0767 - categorical_accuracy: 0.9722 - val_loss: 1.9234 - val_categorical_accuracy: 0.7976 - 484ms/epoch - 9ms/step
Epoch 834/1500
51/51 - 1s - loss: 0.0838 - categorical_accuracy: 0.9694 - val_loss: 1.9352 - val_categorical_accuracy: 0.7981 - 505ms/epoch - 10ms/step
Epoch 835/1500
51/51 - 0s - loss: 0.2720 - categorical_accuracy: 0.9245 - val_loss: 1.5976 - val_categorical_accuracy: 0.7898 - 490ms/epoch - 10ms/step
Epoch 836/1500
51/51 - 1s - loss: 0.0934 - categorical_accuracy: 0.9665 - val_loss: 1.7742 - val_categorical_accuracy: 0.7900 - 524ms/epoch - 10ms/step
Epoch 837/1500
51/51 - 0s - loss: 0.0774 - categorical_accuracy: 0.9716 - val_loss: 1.7927 - val_categorical_accuracy: 0.7969 - 490ms/epoch - 10ms/step
Epoch 838/1500
51/51 - 1s - loss: 0.0772 - categorical_accuracy: 0.9713 - val_loss: 1.8102 - val_categorical_accuracy: 0.8008 - 523ms/epoch - 10ms/step
Epoch 839/1500
51/51 - 0s - loss: 0.0746 - categorical_accuracy: 0.9717 - val_loss: 1.9041 - val_categorical_accuracy: 0.8049 - 484ms/epoch - 9ms/step
Epoch 840/1500
51/51 - 1s - loss: 0.0790 - categorical_accuracy: 0.9710 - val_loss: 1.8386 - val_categorical_accuracy: 0.7968 - 530ms/epoch - 10ms/step
Epoch 841/1500
51/51 - 0s - loss: 0.0787 - categorical_accuracy: 0.9710 - val_loss: 1.8512 - val_categorical_accuracy: 0.7906 - 484ms/epoch - 9ms/step
Epoch 842/1500
51/51 - 1s - loss: 0.0753 - categorical_accuracy: 0.9715 - val_loss: 1.8571 - val_categorical_accuracy: 0.8008 - 540ms/epoch - 11ms/step
Epoch 843/1500
51/51 - 1s - loss: 0.0760 - categorical_accuracy: 0.9713 - val_loss: 1.8797 - val_categorical_accuracy: 0.7954 - 512ms/epoch - 10ms/step
Epoch 844/1500
51/51 - 1s - loss: 0.0798 - categorical_accuracy: 0.9707 - val_loss: 1.9234 - val_categorical_accuracy: 0.7995 - 528ms/epoch - 10ms/step
Epoch 845/1500
51/51 - 0s - loss: 0.0809 - categorical_accuracy: 0.9698 - val_loss: 1.9055 - val_categorical_accuracy: 0.8010 - 493ms/epoch - 10ms/step
Epoch 846/1500
51/51 - 1s - loss: 0.0788 - categorical_accuracy: 0.9706 - val_loss: 1.9803 - val_categorical_accuracy: 0.7973 - 568ms/epoch - 11ms/step
Epoch 847/1500
51/51 - 1s - loss: 0.0773 - categorical_accuracy: 0.9719 - val_loss: 1.9411 - val_categorical_accuracy: 0.7953 - 540ms/epoch - 11ms/step
Epoch 848/1500
51/51 - 1s - loss: 0.0757 - categorical_accuracy: 0.9710 - val_loss: 1.9329 - val_categorical_accuracy: 0.7995 - 572ms/epoch - 11ms/step
Epoch 849/1500
51/51 - 1s - loss: 0.3241 - categorical_accuracy: 0.9199 - val_loss: 1.5062 - val_categorical_accuracy: 0.7957 - 539ms/epoch - 11ms/step
Epoch 850/1500
51/51 - 1s - loss: 0.1004 - categorical_accuracy: 0.9632 - val_loss: 1.6852 - val_categorical_accuracy: 0.7964 - 536ms/epoch - 11ms/step
Epoch 851/1500
51/51 - 1s - loss: 0.0776 - categorical_accuracy: 0.9719 - val_loss: 1.7373 - val_categorical_accuracy: 0.8008 - 517ms/epoch - 10ms/step
Epoch 852/1500
51/51 - 0s - loss: 0.0730 - categorical_accuracy: 0.9725 - val_loss: 1.7862 - val_categorical_accuracy: 0.7981 - 486ms/epoch - 10ms/step
Epoch 853/1500
51/51 - 1s - loss: 0.0735 - categorical_accuracy: 0.9728 - val_loss: 1.8069 - val_categorical_accuracy: 0.7853 - 537ms/epoch - 11ms/step
Epoch 854/1500
51/51 - 1s - loss: 0.0738 - categorical_accuracy: 0.9727 - val_loss: 1.8475 - val_categorical_accuracy: 0.7971 - 505ms/epoch - 10ms/step
Epoch 855/1500
51/51 - 1s - loss: 0.0712 - categorical_accuracy: 0.9734 - val_loss: 1.8655 - val_categorical_accuracy: 0.7961 - 527ms/epoch - 10ms/step
Epoch 856/1500
51/51 - 0s - loss: 0.0736 - categorical_accuracy: 0.9724 - val_loss: 1.8680 - val_categorical_accuracy: 0.7995 - 482ms/epoch - 9ms/step
Epoch 857/1500
51/51 - 1s - loss: 0.0733 - categorical_accuracy: 0.9728 - val_loss: 1.8705 - val_categorical_accuracy: 0.7930 - 525ms/epoch - 10ms/step
Epoch 858/1500
51/51 - 0s - loss: 0.0748 - categorical_accuracy: 0.9721 - val_loss: 1.9089 - val_categorical_accuracy: 0.8027 - 471ms/epoch - 9ms/step
Epoch 859/1500
51/51 - 1s - loss: 0.0747 - categorical_accuracy: 0.9717 - val_loss: 1.8981 - val_categorical_accuracy: 0.7957 - 537ms/epoch - 11ms/step
Epoch 860/1500
51/51 - 0s - loss: 0.0747 - categorical_accuracy: 0.9714 - val_loss: 1.9366 - val_categorical_accuracy: 0.7961 - 496ms/epoch - 10ms/step
Epoch 861/1500
51/51 - 1s - loss: 0.0742 - categorical_accuracy: 0.9721 - val_loss: 1.9318 - val_categorical_accuracy: 0.7926 - 520ms/epoch - 10ms/step
Epoch 862/1500
51/51 - 0s - loss: 0.0787 - categorical_accuracy: 0.9706 - val_loss: 1.9795 - val_categorical_accuracy: 0.7962 - 489ms/epoch - 10ms/step
Epoch 863/1500
51/51 - 1s - loss: 0.0833 - categorical_accuracy: 0.9698 - val_loss: 2.0002 - val_categorical_accuracy: 0.7941 - 518ms/epoch - 10ms/step
Epoch 864/1500
51/51 - 0s - loss: 0.0811 - categorical_accuracy: 0.9703 - val_loss: 1.9215 - val_categorical_accuracy: 0.7932 - 472ms/epoch - 9ms/step
Epoch 865/1500
51/51 - 1s - loss: 0.0787 - categorical_accuracy: 0.9707 - val_loss: 1.9831 - val_categorical_accuracy: 0.7927 - 560ms/epoch - 11ms/step
Epoch 866/1500
51/51 - 0s - loss: 0.0833 - categorical_accuracy: 0.9685 - val_loss: 1.9166 - val_categorical_accuracy: 0.7930 - 479ms/epoch - 9ms/step
Epoch 867/1500
51/51 - 1s - loss: 0.0748 - categorical_accuracy: 0.9720 - val_loss: 1.9622 - val_categorical_accuracy: 0.7983 - 523ms/epoch - 10ms/step
Epoch 868/1500
51/51 - 0s - loss: 0.0775 - categorical_accuracy: 0.9713 - val_loss: 1.9966 - val_categorical_accuracy: 0.7925 - 484ms/epoch - 9ms/step
Epoch 869/1500
51/51 - 1s - loss: 0.0747 - categorical_accuracy: 0.9718 - val_loss: 1.9904 - val_categorical_accuracy: 0.7964 - 526ms/epoch - 10ms/step
Epoch 870/1500
51/51 - 0s - loss: 0.0827 - categorical_accuracy: 0.9690 - val_loss: 1.9228 - val_categorical_accuracy: 0.7883 - 480ms/epoch - 9ms/step
Epoch 871/1500
51/51 - 1s - loss: 0.0898 - categorical_accuracy: 0.9672 - val_loss: 1.9797 - val_categorical_accuracy: 0.7855 - 524ms/epoch - 10ms/step
Epoch 872/1500
51/51 - 0s - loss: 0.0887 - categorical_accuracy: 0.9678 - val_loss: 1.9268 - val_categorical_accuracy: 0.8020 - 489ms/epoch - 10ms/step
Epoch 873/1500
51/51 - 1s - loss: 0.0836 - categorical_accuracy: 0.9681 - val_loss: 2.0004 - val_categorical_accuracy: 0.7815 - 542ms/epoch - 11ms/step
Epoch 874/1500
51/51 - 0s - loss: 0.0896 - categorical_accuracy: 0.9665 - val_loss: 1.9917 - val_categorical_accuracy: 0.7955 - 487ms/epoch - 10ms/step
Epoch 875/1500
51/51 - 1s - loss: 0.0760 - categorical_accuracy: 0.9722 - val_loss: 2.0371 - val_categorical_accuracy: 0.8059 - 516ms/epoch - 10ms/step
Epoch 876/1500
51/51 - 0s - loss: 0.0784 - categorical_accuracy: 0.9704 - val_loss: 1.9989 - val_categorical_accuracy: 0.8032 - 486ms/epoch - 10ms/step
Epoch 877/1500
51/51 - 1s - loss: 0.0748 - categorical_accuracy: 0.9724 - val_loss: 2.0011 - val_categorical_accuracy: 0.8004 - 512ms/epoch - 10ms/step
Epoch 878/1500
51/51 - 0s - loss: 0.0776 - categorical_accuracy: 0.9707 - val_loss: 1.9508 - val_categorical_accuracy: 0.7980 - 496ms/epoch - 10ms/step
Epoch 879/1500
51/51 - 1s - loss: 0.0783 - categorical_accuracy: 0.9705 - val_loss: 2.0076 - val_categorical_accuracy: 0.7991 - 527ms/epoch - 10ms/step
Epoch 880/1500
51/51 - 1s - loss: 0.0823 - categorical_accuracy: 0.9697 - val_loss: 1.9884 - val_categorical_accuracy: 0.7913 - 503ms/epoch - 10ms/step
Epoch 881/1500
51/51 - 1s - loss: 0.0840 - categorical_accuracy: 0.9678 - val_loss: 1.9745 - val_categorical_accuracy: 0.7990 - 512ms/epoch - 10ms/step
Epoch 882/1500
51/51 - 0s - loss: 0.2028 - categorical_accuracy: 0.9492 - val_loss: 2.1057 - val_categorical_accuracy: 0.5812 - 499ms/epoch - 10ms/step
Epoch 883/1500
51/51 - 1s - loss: 0.2240 - categorical_accuracy: 0.9252 - val_loss: 1.7027 - val_categorical_accuracy: 0.7959 - 529ms/epoch - 10ms/step
Epoch 884/1500
51/51 - 1s - loss: 0.0960 - categorical_accuracy: 0.9653 - val_loss: 1.8269 - val_categorical_accuracy: 0.7872 - 507ms/epoch - 10ms/step
Epoch 885/1500
51/51 - 1s - loss: 0.2216 - categorical_accuracy: 0.9355 - val_loss: 1.6917 - val_categorical_accuracy: 0.7899 - 524ms/epoch - 10ms/step
Epoch 886/1500
51/51 - 1s - loss: 0.0876 - categorical_accuracy: 0.9672 - val_loss: 1.7747 - val_categorical_accuracy: 0.7957 - 500ms/epoch - 10ms/step
Epoch 887/1500
51/51 - 1s - loss: 0.0776 - categorical_accuracy: 0.9715 - val_loss: 1.7456 - val_categorical_accuracy: 0.8047 - 516ms/epoch - 10ms/step
Epoch 888/1500
51/51 - 1s - loss: 0.0758 - categorical_accuracy: 0.9723 - val_loss: 1.8125 - val_categorical_accuracy: 0.7986 - 526ms/epoch - 10ms/step
Epoch 889/1500
51/51 - 0s - loss: 0.0749 - categorical_accuracy: 0.9717 - val_loss: 1.7886 - val_categorical_accuracy: 0.7932 - 491ms/epoch - 10ms/step
Epoch 890/1500
51/51 - 1s - loss: 0.0735 - categorical_accuracy: 0.9718 - val_loss: 1.8203 - val_categorical_accuracy: 0.7935 - 507ms/epoch - 10ms/step
Epoch 891/1500
51/51 - 1s - loss: 0.0812 - categorical_accuracy: 0.9694 - val_loss: 1.9025 - val_categorical_accuracy: 0.8016 - 525ms/epoch - 10ms/step
Epoch 892/1500
51/51 - 1s - loss: 0.0754 - categorical_accuracy: 0.9714 - val_loss: 1.8788 - val_categorical_accuracy: 0.7944 - 861ms/epoch - 17ms/step
Epoch 893/1500
51/51 - 1s - loss: 0.0746 - categorical_accuracy: 0.9717 - val_loss: 1.9086 - val_categorical_accuracy: 0.7961 - 569ms/epoch - 11ms/step
Epoch 894/1500
51/51 - 1s - loss: 0.0706 - categorical_accuracy: 0.9734 - val_loss: 1.9510 - val_categorical_accuracy: 0.8044 - 521ms/epoch - 10ms/step
Epoch 895/1500
51/51 - 1s - loss: 0.0715 - categorical_accuracy: 0.9732 - val_loss: 1.9240 - val_categorical_accuracy: 0.7961 - 530ms/epoch - 10ms/step
Epoch 896/1500
51/51 - 1s - loss: 0.0702 - categorical_accuracy: 0.9738 - val_loss: 1.9501 - val_categorical_accuracy: 0.7999 - 527ms/epoch - 10ms/step
Epoch 897/1500
51/51 - 1s - loss: 0.0687 - categorical_accuracy: 0.9746 - val_loss: 1.9555 - val_categorical_accuracy: 0.7989 - 533ms/epoch - 10ms/step
Epoch 898/1500
51/51 - 1s - loss: 0.0744 - categorical_accuracy: 0.9719 - val_loss: 1.9707 - val_categorical_accuracy: 0.8010 - 522ms/epoch - 10ms/step
Epoch 899/1500
51/51 - 1s - loss: 0.0741 - categorical_accuracy: 0.9717 - val_loss: 1.9699 - val_categorical_accuracy: 0.7853 - 565ms/epoch - 11ms/step
Epoch 900/1500
51/51 - 1s - loss: 0.0798 - categorical_accuracy: 0.9702 - val_loss: 1.9528 - val_categorical_accuracy: 0.7991 - 505ms/epoch - 10ms/step
Epoch 901/1500
51/51 - 1s - loss: 0.0822 - categorical_accuracy: 0.9695 - val_loss: 2.0271 - val_categorical_accuracy: 0.8019 - 549ms/epoch - 11ms/step
Epoch 902/1500
51/51 - 0s - loss: 0.0862 - categorical_accuracy: 0.9682 - val_loss: 1.9257 - val_categorical_accuracy: 0.7890 - 494ms/epoch - 10ms/step
Epoch 903/1500
51/51 - 1s - loss: 0.0765 - categorical_accuracy: 0.9709 - val_loss: 2.0226 - val_categorical_accuracy: 0.7945 - 577ms/epoch - 11ms/step
Epoch 904/1500
51/51 - 1s - loss: 0.0799 - categorical_accuracy: 0.9691 - val_loss: 1.9645 - val_categorical_accuracy: 0.7822 - 500ms/epoch - 10ms/step
Epoch 905/1500
51/51 - 1s - loss: 0.0803 - categorical_accuracy: 0.9701 - val_loss: 1.9803 - val_categorical_accuracy: 0.7921 - 538ms/epoch - 11ms/step
Epoch 906/1500
51/51 - 1s - loss: 0.0846 - categorical_accuracy: 0.9696 - val_loss: 2.0678 - val_categorical_accuracy: 0.7876 - 510ms/epoch - 10ms/step
Epoch 907/1500
51/51 - 1s - loss: 0.0757 - categorical_accuracy: 0.9721 - val_loss: 1.9901 - val_categorical_accuracy: 0.7984 - 553ms/epoch - 11ms/step
Epoch 908/1500
51/51 - 1s - loss: 0.0795 - categorical_accuracy: 0.9694 - val_loss: 1.9655 - val_categorical_accuracy: 0.7880 - 530ms/epoch - 10ms/step
Epoch 909/1500
51/51 - 1s - loss: 0.0802 - categorical_accuracy: 0.9700 - val_loss: 2.0631 - val_categorical_accuracy: 0.7869 - 525ms/epoch - 10ms/step
Epoch 910/1500
51/51 - 1s - loss: 0.0823 - categorical_accuracy: 0.9696 - val_loss: 1.9611 - val_categorical_accuracy: 0.7994 - 532ms/epoch - 10ms/step
Epoch 911/1500
51/51 - 1s - loss: 0.0704 - categorical_accuracy: 0.9738 - val_loss: 1.9639 - val_categorical_accuracy: 0.7973 - 501ms/epoch - 10ms/step
Epoch 912/1500
51/51 - 1s - loss: 0.0690 - categorical_accuracy: 0.9737 - val_loss: 1.9775 - val_categorical_accuracy: 0.7976 - 534ms/epoch - 10ms/step
Epoch 913/1500
51/51 - 1s - loss: 0.0729 - categorical_accuracy: 0.9728 - val_loss: 2.0199 - val_categorical_accuracy: 0.7955 - 534ms/epoch - 10ms/step
Epoch 914/1500
51/51 - 1s - loss: 0.0812 - categorical_accuracy: 0.9692 - val_loss: 2.0230 - val_categorical_accuracy: 0.7974 - 558ms/epoch - 11ms/step
Epoch 915/1500
51/51 - 1s - loss: 0.0724 - categorical_accuracy: 0.9727 - val_loss: 2.0977 - val_categorical_accuracy: 0.7881 - 511ms/epoch - 10ms/step
Epoch 916/1500
51/51 - 1s - loss: 0.0840 - categorical_accuracy: 0.9692 - val_loss: 2.1261 - val_categorical_accuracy: 0.7852 - 545ms/epoch - 11ms/step
Epoch 917/1500
51/51 - 0s - loss: 0.4979 - categorical_accuracy: 0.8810 - val_loss: 1.5741 - val_categorical_accuracy: 0.7826 - 487ms/epoch - 10ms/step
Epoch 918/1500
51/51 - 1s - loss: 0.1021 - categorical_accuracy: 0.9633 - val_loss: 1.6973 - val_categorical_accuracy: 0.7921 - 541ms/epoch - 11ms/step
Epoch 919/1500
51/51 - 0s - loss: 0.0792 - categorical_accuracy: 0.9708 - val_loss: 1.7800 - val_categorical_accuracy: 0.7995 - 495ms/epoch - 10ms/step
Epoch 920/1500
51/51 - 1s - loss: 0.0748 - categorical_accuracy: 0.9726 - val_loss: 1.8459 - val_categorical_accuracy: 0.8014 - 549ms/epoch - 11ms/step
Epoch 921/1500
51/51 - 1s - loss: 0.0699 - categorical_accuracy: 0.9744 - val_loss: 1.8604 - val_categorical_accuracy: 0.7999 - 511ms/epoch - 10ms/step
Epoch 922/1500
51/51 - 1s - loss: 0.0715 - categorical_accuracy: 0.9734 - val_loss: 1.8292 - val_categorical_accuracy: 0.7940 - 546ms/epoch - 11ms/step
Epoch 923/1500
51/51 - 1s - loss: 0.0732 - categorical_accuracy: 0.9725 - val_loss: 1.9189 - val_categorical_accuracy: 0.8001 - 510ms/epoch - 10ms/step
Epoch 924/1500
51/51 - 1s - loss: 0.0698 - categorical_accuracy: 0.9738 - val_loss: 1.9590 - val_categorical_accuracy: 0.7980 - 536ms/epoch - 11ms/step
Epoch 925/1500
51/51 - 1s - loss: 0.0713 - categorical_accuracy: 0.9733 - val_loss: 1.9680 - val_categorical_accuracy: 0.8000 - 520ms/epoch - 10ms/step
Epoch 926/1500
51/51 - 1s - loss: 0.0698 - categorical_accuracy: 0.9735 - val_loss: 1.9550 - val_categorical_accuracy: 0.7936 - 520ms/epoch - 10ms/step
Epoch 927/1500
51/51 - 1s - loss: 0.0727 - categorical_accuracy: 0.9724 - val_loss: 1.9806 - val_categorical_accuracy: 0.7967 - 526ms/epoch - 10ms/step
Epoch 928/1500
51/51 - 1s - loss: 0.0711 - categorical_accuracy: 0.9733 - val_loss: 2.0206 - val_categorical_accuracy: 0.7966 - 525ms/epoch - 10ms/step
Epoch 929/1500
51/51 - 1s - loss: 0.0704 - categorical_accuracy: 0.9729 - val_loss: 2.0353 - val_categorical_accuracy: 0.7876 - 506ms/epoch - 10ms/step
Epoch 930/1500
51/51 - 1s - loss: 0.0788 - categorical_accuracy: 0.9709 - val_loss: 1.9880 - val_categorical_accuracy: 0.7989 - 525ms/epoch - 10ms/step
Epoch 931/1500
51/51 - 1s - loss: 0.0734 - categorical_accuracy: 0.9723 - val_loss: 2.0056 - val_categorical_accuracy: 0.8005 - 536ms/epoch - 11ms/step
Epoch 932/1500
51/51 - 1s - loss: 0.0759 - categorical_accuracy: 0.9720 - val_loss: 2.0179 - val_categorical_accuracy: 0.7968 - 526ms/epoch - 10ms/step
Epoch 933/1500
51/51 - 1s - loss: 0.0764 - categorical_accuracy: 0.9711 - val_loss: 2.0026 - val_categorical_accuracy: 0.8022 - 581ms/epoch - 11ms/step
Epoch 934/1500
51/51 - 1s - loss: 0.0684 - categorical_accuracy: 0.9741 - val_loss: 2.0442 - val_categorical_accuracy: 0.7870 - 520ms/epoch - 10ms/step
Epoch 935/1500
51/51 - 1s - loss: 0.0664 - categorical_accuracy: 0.9746 - val_loss: 2.0614 - val_categorical_accuracy: 0.8000 - 567ms/epoch - 11ms/step
Epoch 936/1500
51/51 - 1s - loss: 0.0679 - categorical_accuracy: 0.9736 - val_loss: 2.0661 - val_categorical_accuracy: 0.8000 - 539ms/epoch - 11ms/step
Epoch 937/1500
51/51 - 1s - loss: 0.0822 - categorical_accuracy: 0.9692 - val_loss: 2.1163 - val_categorical_accuracy: 0.7780 - 587ms/epoch - 12ms/step
Epoch 938/1500
51/51 - 1s - loss: 0.1937 - categorical_accuracy: 0.9397 - val_loss: 1.9283 - val_categorical_accuracy: 0.7894 - 571ms/epoch - 11ms/step
Epoch 939/1500
51/51 - 1s - loss: 0.0913 - categorical_accuracy: 0.9651 - val_loss: 1.9975 - val_categorical_accuracy: 0.7835 - 573ms/epoch - 11ms/step
Epoch 940/1500
51/51 - 1s - loss: 0.0960 - categorical_accuracy: 0.9634 - val_loss: 2.0446 - val_categorical_accuracy: 0.7882 - 595ms/epoch - 12ms/step
Epoch 941/1500
51/51 - 1s - loss: 0.1030 - categorical_accuracy: 0.9618 - val_loss: 1.8987 - val_categorical_accuracy: 0.7958 - 558ms/epoch - 11ms/step
Epoch 942/1500
51/51 - 1s - loss: 0.0753 - categorical_accuracy: 0.9721 - val_loss: 1.9644 - val_categorical_accuracy: 0.8029 - 592ms/epoch - 12ms/step
Epoch 943/1500
51/51 - 1s - loss: 0.0753 - categorical_accuracy: 0.9729 - val_loss: 1.9692 - val_categorical_accuracy: 0.7960 - 564ms/epoch - 11ms/step
Epoch 944/1500
51/51 - 1s - loss: 0.0724 - categorical_accuracy: 0.9728 - val_loss: 2.0221 - val_categorical_accuracy: 0.7827 - 575ms/epoch - 11ms/step
Epoch 945/1500
51/51 - 1s - loss: 0.0817 - categorical_accuracy: 0.9694 - val_loss: 1.9709 - val_categorical_accuracy: 0.7931 - 556ms/epoch - 11ms/step
Epoch 946/1500
51/51 - 1s - loss: 0.0721 - categorical_accuracy: 0.9733 - val_loss: 2.0827 - val_categorical_accuracy: 0.7879 - 551ms/epoch - 11ms/step
Epoch 947/1500
51/51 - 1s - loss: 0.0805 - categorical_accuracy: 0.9693 - val_loss: 2.0031 - val_categorical_accuracy: 0.8032 - 561ms/epoch - 11ms/step
Epoch 948/1500
51/51 - 1s - loss: 0.0724 - categorical_accuracy: 0.9734 - val_loss: 2.0710 - val_categorical_accuracy: 0.8004 - 577ms/epoch - 11ms/step
Epoch 949/1500
51/51 - 1s - loss: 0.0737 - categorical_accuracy: 0.9725 - val_loss: 1.9970 - val_categorical_accuracy: 0.8033 - 597ms/epoch - 12ms/step
Epoch 950/1500
51/51 - 1s - loss: 0.0742 - categorical_accuracy: 0.9710 - val_loss: 2.0251 - val_categorical_accuracy: 0.7967 - 539ms/epoch - 11ms/step
Epoch 951/1500
51/51 - 1s - loss: 0.0824 - categorical_accuracy: 0.9687 - val_loss: 2.0036 - val_categorical_accuracy: 0.7929 - 573ms/epoch - 11ms/step
Epoch 952/1500
51/51 - 1s - loss: 0.0730 - categorical_accuracy: 0.9733 - val_loss: 2.0332 - val_categorical_accuracy: 0.7963 - 562ms/epoch - 11ms/step
Epoch 953/1500
51/51 - 1s - loss: 0.0703 - categorical_accuracy: 0.9735 - val_loss: 2.0868 - val_categorical_accuracy: 0.7876 - 577ms/epoch - 11ms/step
Epoch 954/1500
51/51 - 1s - loss: 0.0770 - categorical_accuracy: 0.9707 - val_loss: 2.1489 - val_categorical_accuracy: 0.7794 - 594ms/epoch - 12ms/step
Epoch 955/1500
51/51 - 1s - loss: 0.0801 - categorical_accuracy: 0.9704 - val_loss: 2.1442 - val_categorical_accuracy: 0.7991 - 565ms/epoch - 11ms/step
Epoch 956/1500
51/51 - 1s - loss: 0.0791 - categorical_accuracy: 0.9710 - val_loss: 2.0559 - val_categorical_accuracy: 0.7976 - 571ms/epoch - 11ms/step
Epoch 957/1500
51/51 - 1s - loss: 0.0735 - categorical_accuracy: 0.9729 - val_loss: 2.0034 - val_categorical_accuracy: 0.7921 - 544ms/epoch - 11ms/step
Epoch 958/1500
51/51 - 1s - loss: 0.0822 - categorical_accuracy: 0.9698 - val_loss: 2.0244 - val_categorical_accuracy: 0.7847 - 605ms/epoch - 12ms/step
Epoch 959/1500
51/51 - 1s - loss: 0.0854 - categorical_accuracy: 0.9682 - val_loss: 2.0452 - val_categorical_accuracy: 0.7961 - 574ms/epoch - 11ms/step
Epoch 960/1500
51/51 - 1s - loss: 0.0718 - categorical_accuracy: 0.9732 - val_loss: 2.1171 - val_categorical_accuracy: 0.7911 - 569ms/epoch - 11ms/step
Epoch 961/1500
51/51 - 1s - loss: 0.0695 - categorical_accuracy: 0.9740 - val_loss: 2.0891 - val_categorical_accuracy: 0.7976 - 575ms/epoch - 11ms/step
Epoch 962/1500
51/51 - 1s - loss: 0.0696 - categorical_accuracy: 0.9740 - val_loss: 2.0935 - val_categorical_accuracy: 0.7936 - 511ms/epoch - 10ms/step
Epoch 963/1500
51/51 - 1s - loss: 0.0677 - categorical_accuracy: 0.9750 - val_loss: 2.1159 - val_categorical_accuracy: 0.7943 - 583ms/epoch - 11ms/step
Epoch 964/1500
51/51 - 1s - loss: 0.0695 - categorical_accuracy: 0.9733 - val_loss: 2.1133 - val_categorical_accuracy: 0.7901 - 542ms/epoch - 11ms/step
Epoch 965/1500
51/51 - 1s - loss: 0.0677 - categorical_accuracy: 0.9745 - val_loss: 2.1736 - val_categorical_accuracy: 0.7827 - 568ms/epoch - 11ms/step
Epoch 966/1500
51/51 - 1s - loss: 0.3253 - categorical_accuracy: 0.9145 - val_loss: 1.7375 - val_categorical_accuracy: 0.7938 - 552ms/epoch - 11ms/step
Epoch 967/1500
51/51 - 1s - loss: 0.0841 - categorical_accuracy: 0.9688 - val_loss: 1.8484 - val_categorical_accuracy: 0.7998 - 566ms/epoch - 11ms/step
Epoch 968/1500
51/51 - 1s - loss: 0.0723 - categorical_accuracy: 0.9734 - val_loss: 1.9219 - val_categorical_accuracy: 0.7952 - 574ms/epoch - 11ms/step
Epoch 969/1500
51/51 - 1s - loss: 0.0675 - categorical_accuracy: 0.9745 - val_loss: 1.9920 - val_categorical_accuracy: 0.7981 - 560ms/epoch - 11ms/step
Epoch 970/1500
51/51 - 1s - loss: 0.0702 - categorical_accuracy: 0.9734 - val_loss: 2.0112 - val_categorical_accuracy: 0.7975 - 595ms/epoch - 12ms/step
Epoch 971/1500
51/51 - 1s - loss: 0.0737 - categorical_accuracy: 0.9732 - val_loss: 1.9924 - val_categorical_accuracy: 0.7910 - 540ms/epoch - 11ms/step
Epoch 972/1500
51/51 - 1s - loss: 0.0789 - categorical_accuracy: 0.9693 - val_loss: 1.9986 - val_categorical_accuracy: 0.8004 - 586ms/epoch - 11ms/step
Epoch 973/1500
51/51 - 1s - loss: 0.0720 - categorical_accuracy: 0.9729 - val_loss: 1.9846 - val_categorical_accuracy: 0.7974 - 530ms/epoch - 10ms/step
Epoch 974/1500
51/51 - 1s - loss: 0.0689 - categorical_accuracy: 0.9736 - val_loss: 2.0732 - val_categorical_accuracy: 0.7890 - 555ms/epoch - 11ms/step
Epoch 975/1500
51/51 - 1s - loss: 0.0711 - categorical_accuracy: 0.9735 - val_loss: 2.0499 - val_categorical_accuracy: 0.7925 - 597ms/epoch - 12ms/step
Epoch 976/1500
51/51 - 1s - loss: 0.0717 - categorical_accuracy: 0.9734 - val_loss: 2.0770 - val_categorical_accuracy: 0.8007 - 559ms/epoch - 11ms/step
Epoch 977/1500
51/51 - 1s - loss: 0.0753 - categorical_accuracy: 0.9721 - val_loss: 2.0657 - val_categorical_accuracy: 0.7988 - 589ms/epoch - 12ms/step
Epoch 978/1500
51/51 - 1s - loss: 0.0704 - categorical_accuracy: 0.9732 - val_loss: 2.0888 - val_categorical_accuracy: 0.7933 - 527ms/epoch - 10ms/step
Epoch 979/1500
51/51 - 1s - loss: 0.0721 - categorical_accuracy: 0.9729 - val_loss: 2.0315 - val_categorical_accuracy: 0.7902 - 593ms/epoch - 12ms/step
Epoch 980/1500
51/51 - 1s - loss: 0.0689 - categorical_accuracy: 0.9745 - val_loss: 2.0790 - val_categorical_accuracy: 0.7916 - 538ms/epoch - 11ms/step
Epoch 981/1500
51/51 - 1s - loss: 0.0657 - categorical_accuracy: 0.9754 - val_loss: 2.1026 - val_categorical_accuracy: 0.7920 - 573ms/epoch - 11ms/step
Epoch 982/1500
51/51 - 1s - loss: 0.0701 - categorical_accuracy: 0.9741 - val_loss: 2.0963 - val_categorical_accuracy: 0.7893 - 566ms/epoch - 11ms/step
Epoch 983/1500
51/51 - 1s - loss: 0.0763 - categorical_accuracy: 0.9709 - val_loss: 2.1020 - val_categorical_accuracy: 0.7872 - 572ms/epoch - 11ms/step
Epoch 984/1500
51/51 - 1s - loss: 0.0847 - categorical_accuracy: 0.9688 - val_loss: 2.0979 - val_categorical_accuracy: 0.7856 - 553ms/epoch - 11ms/step
Epoch 985/1500
51/51 - 1s - loss: 0.0818 - categorical_accuracy: 0.9678 - val_loss: 2.0890 - val_categorical_accuracy: 0.8019 - 554ms/epoch - 11ms/step
Epoch 986/1500
51/51 - 1s - loss: 0.0748 - categorical_accuracy: 0.9712 - val_loss: 2.1635 - val_categorical_accuracy: 0.7990 - 576ms/epoch - 11ms/step
Epoch 987/1500
51/51 - 1s - loss: 0.4262 - categorical_accuracy: 0.8945 - val_loss: 1.7333 - val_categorical_accuracy: 0.7640 - 556ms/epoch - 11ms/step
Epoch 988/1500
51/51 - 1s - loss: 0.1275 - categorical_accuracy: 0.9534 - val_loss: 1.7255 - val_categorical_accuracy: 0.7908 - 580ms/epoch - 11ms/step
Epoch 989/1500
51/51 - 1s - loss: 0.0781 - categorical_accuracy: 0.9715 - val_loss: 1.8146 - val_categorical_accuracy: 0.7943 - 545ms/epoch - 11ms/step
Epoch 990/1500
51/51 - 1s - loss: 0.0704 - categorical_accuracy: 0.9734 - val_loss: 1.8322 - val_categorical_accuracy: 0.7989 - 557ms/epoch - 11ms/step
Epoch 991/1500
51/51 - 1s - loss: 0.0702 - categorical_accuracy: 0.9738 - val_loss: 1.8860 - val_categorical_accuracy: 0.7938 - 571ms/epoch - 11ms/step
Epoch 992/1500
51/51 - 1s - loss: 0.0653 - categorical_accuracy: 0.9754 - val_loss: 1.9795 - val_categorical_accuracy: 0.7996 - 540ms/epoch - 11ms/step
Epoch 993/1500
51/51 - 1s - loss: 0.0673 - categorical_accuracy: 0.9752 - val_loss: 1.9446 - val_categorical_accuracy: 0.7946 - 590ms/epoch - 12ms/step
Epoch 994/1500
51/51 - 1s - loss: 0.0662 - categorical_accuracy: 0.9755 - val_loss: 1.9727 - val_categorical_accuracy: 0.7991 - 505ms/epoch - 10ms/step
Epoch 995/1500
51/51 - 1s - loss: 0.0683 - categorical_accuracy: 0.9746 - val_loss: 1.9698 - val_categorical_accuracy: 0.7930 - 521ms/epoch - 10ms/step
Epoch 996/1500
51/51 - 1s - loss: 0.0679 - categorical_accuracy: 0.9753 - val_loss: 2.0364 - val_categorical_accuracy: 0.7967 - 512ms/epoch - 10ms/step
Epoch 997/1500
51/51 - 1s - loss: 0.0669 - categorical_accuracy: 0.9748 - val_loss: 2.0185 - val_categorical_accuracy: 0.7989 - 538ms/epoch - 11ms/step
Epoch 998/1500
51/51 - 1s - loss: 0.0684 - categorical_accuracy: 0.9733 - val_loss: 2.0144 - val_categorical_accuracy: 0.7961 - 537ms/epoch - 11ms/step
Epoch 999/1500
51/51 - 1s - loss: 0.0851 - categorical_accuracy: 0.9686 - val_loss: 1.9621 - val_categorical_accuracy: 0.7805 - 541ms/epoch - 11ms/step
Epoch 1000/1500
51/51 - 1s - loss: 0.2636 - categorical_accuracy: 0.9258 - val_loss: 1.8341 - val_categorical_accuracy: 0.8014 - 526ms/epoch - 10ms/step
Epoch 1001/1500
51/51 - 1s - loss: 0.0852 - categorical_accuracy: 0.9683 - val_loss: 1.8705 - val_categorical_accuracy: 0.7892 - 535ms/epoch - 10ms/step
Epoch 1002/1500
51/51 - 1s - loss: 0.0748 - categorical_accuracy: 0.9724 - val_loss: 1.8884 - val_categorical_accuracy: 0.8011 - 509ms/epoch - 10ms/step
Epoch 1003/1500
51/51 - 1s - loss: 0.0695 - categorical_accuracy: 0.9741 - val_loss: 1.9972 - val_categorical_accuracy: 0.7983 - 509ms/epoch - 10ms/step
Epoch 1004/1500
51/51 - 1s - loss: 0.0680 - categorical_accuracy: 0.9748 - val_loss: 2.0121 - val_categorical_accuracy: 0.7983 - 525ms/epoch - 10ms/step
Epoch 1005/1500
51/51 - 1s - loss: 0.0724 - categorical_accuracy: 0.9737 - val_loss: 1.9794 - val_categorical_accuracy: 0.7881 - 520ms/epoch - 10ms/step
Epoch 1006/1500
51/51 - 1s - loss: 0.0661 - categorical_accuracy: 0.9748 - val_loss: 2.0294 - val_categorical_accuracy: 0.7874 - 535ms/epoch - 10ms/step
Epoch 1007/1500
51/51 - 0s - loss: 0.0676 - categorical_accuracy: 0.9756 - val_loss: 1.9796 - val_categorical_accuracy: 0.7921 - 495ms/epoch - 10ms/step
Epoch 1008/1500
51/51 - 1s - loss: 0.0698 - categorical_accuracy: 0.9739 - val_loss: 1.9980 - val_categorical_accuracy: 0.7952 - 524ms/epoch - 10ms/step
Epoch 1009/1500
51/51 - 1s - loss: 0.0728 - categorical_accuracy: 0.9723 - val_loss: 2.0625 - val_categorical_accuracy: 0.7964 - 504ms/epoch - 10ms/step
Epoch 1010/1500
51/51 - 1s - loss: 0.0732 - categorical_accuracy: 0.9726 - val_loss: 1.9886 - val_categorical_accuracy: 0.7867 - 554ms/epoch - 11ms/step
Epoch 1011/1500
51/51 - 1s - loss: 0.0700 - categorical_accuracy: 0.9733 - val_loss: 2.0129 - val_categorical_accuracy: 0.7963 - 517ms/epoch - 10ms/step
Epoch 1012/1500
51/51 - 1s - loss: 0.0675 - categorical_accuracy: 0.9741 - val_loss: 2.0817 - val_categorical_accuracy: 0.7871 - 566ms/epoch - 11ms/step
Epoch 1013/1500
51/51 - 0s - loss: 0.0662 - categorical_accuracy: 0.9748 - val_loss: 2.0315 - val_categorical_accuracy: 0.7836 - 488ms/epoch - 10ms/step
Epoch 1014/1500
51/51 - 1s - loss: 0.0714 - categorical_accuracy: 0.9730 - val_loss: 2.1670 - val_categorical_accuracy: 0.7920 - 556ms/epoch - 11ms/step
Epoch 1015/1500
51/51 - 0s - loss: 0.0694 - categorical_accuracy: 0.9733 - val_loss: 2.0815 - val_categorical_accuracy: 0.7967 - 495ms/epoch - 10ms/step
Epoch 1016/1500
51/51 - 1s - loss: 0.0732 - categorical_accuracy: 0.9726 - val_loss: 2.1941 - val_categorical_accuracy: 0.7971 - 556ms/epoch - 11ms/step
Epoch 1017/1500
51/51 - 1s - loss: 0.0687 - categorical_accuracy: 0.9746 - val_loss: 2.0761 - val_categorical_accuracy: 0.7938 - 507ms/epoch - 10ms/step
Epoch 1018/1500
51/51 - 1s - loss: 0.0654 - categorical_accuracy: 0.9748 - val_loss: 2.0931 - val_categorical_accuracy: 0.7934 - 569ms/epoch - 11ms/step
Epoch 1019/1500
51/51 - 1s - loss: 0.0689 - categorical_accuracy: 0.9752 - val_loss: 2.1187 - val_categorical_accuracy: 0.7974 - 550ms/epoch - 11ms/step
Epoch 1020/1500
51/51 - 1s - loss: 0.0668 - categorical_accuracy: 0.9748 - val_loss: 2.1248 - val_categorical_accuracy: 0.7817 - 567ms/epoch - 11ms/step
Epoch 1021/1500
51/51 - 1s - loss: 0.0696 - categorical_accuracy: 0.9734 - val_loss: 2.1036 - val_categorical_accuracy: 0.7964 - 571ms/epoch - 11ms/step
Epoch 1022/1500
51/51 - 1s - loss: 0.0712 - categorical_accuracy: 0.9727 - val_loss: 2.0382 - val_categorical_accuracy: 0.7877 - 562ms/epoch - 11ms/step
Epoch 1023/1500
51/51 - 1s - loss: 0.0733 - categorical_accuracy: 0.9727 - val_loss: 2.1480 - val_categorical_accuracy: 0.7924 - 596ms/epoch - 12ms/step
Epoch 1024/1500
51/51 - 1s - loss: 0.0736 - categorical_accuracy: 0.9726 - val_loss: 2.1108 - val_categorical_accuracy: 0.7951 - 508ms/epoch - 10ms/step
Epoch 1025/1500
51/51 - 1s - loss: 0.0724 - categorical_accuracy: 0.9719 - val_loss: 2.1029 - val_categorical_accuracy: 0.7904 - 575ms/epoch - 11ms/step
Epoch 1026/1500
51/51 - 1s - loss: 0.0673 - categorical_accuracy: 0.9740 - val_loss: 2.1701 - val_categorical_accuracy: 0.7975 - 555ms/epoch - 11ms/step
Epoch 1027/1500
51/51 - 1s - loss: 0.0690 - categorical_accuracy: 0.9742 - val_loss: 2.1718 - val_categorical_accuracy: 0.7885 - 564ms/epoch - 11ms/step
Epoch 1028/1500
51/51 - 1s - loss: 0.0667 - categorical_accuracy: 0.9747 - val_loss: 2.1339 - val_categorical_accuracy: 0.7909 - 577ms/epoch - 11ms/step
Epoch 1029/1500
51/51 - 1s - loss: 0.0643 - categorical_accuracy: 0.9750 - val_loss: 2.1444 - val_categorical_accuracy: 0.7995 - 553ms/epoch - 11ms/step
Epoch 1030/1500
51/51 - 1s - loss: 0.0655 - categorical_accuracy: 0.9752 - val_loss: 2.1681 - val_categorical_accuracy: 0.7888 - 618ms/epoch - 12ms/step
Epoch 1031/1500
51/51 - 1s - loss: 0.0676 - categorical_accuracy: 0.9749 - val_loss: 2.1653 - val_categorical_accuracy: 0.7884 - 555ms/epoch - 11ms/step
Epoch 1032/1500
51/51 - 1s - loss: 0.0669 - categorical_accuracy: 0.9741 - val_loss: 2.2216 - val_categorical_accuracy: 0.7862 - 573ms/epoch - 11ms/step
Epoch 1033/1500
51/51 - 1s - loss: 0.0793 - categorical_accuracy: 0.9708 - val_loss: 2.3429 - val_categorical_accuracy: 0.7999 - 565ms/epoch - 11ms/step
Epoch 1034/1500
51/51 - 1s - loss: 0.0814 - categorical_accuracy: 0.9694 - val_loss: 2.1558 - val_categorical_accuracy: 0.7953 - 557ms/epoch - 11ms/step
Epoch 1035/1500
51/51 - 1s - loss: 0.0672 - categorical_accuracy: 0.9757 - val_loss: 2.1961 - val_categorical_accuracy: 0.7984 - 542ms/epoch - 11ms/step
Epoch 1036/1500
51/51 - 1s - loss: 0.0706 - categorical_accuracy: 0.9728 - val_loss: 2.1842 - val_categorical_accuracy: 0.7969 - 550ms/epoch - 11ms/step
Epoch 1037/1500
51/51 - 1s - loss: 0.0736 - categorical_accuracy: 0.9719 - val_loss: 2.1424 - val_categorical_accuracy: 0.7883 - 571ms/epoch - 11ms/step
Epoch 1038/1500
51/51 - 1s - loss: 0.0683 - categorical_accuracy: 0.9735 - val_loss: 2.1993 - val_categorical_accuracy: 0.7942 - 555ms/epoch - 11ms/step
Epoch 1039/1500
51/51 - 1s - loss: 0.0692 - categorical_accuracy: 0.9732 - val_loss: 2.1613 - val_categorical_accuracy: 0.7896 - 580ms/epoch - 11ms/step
Epoch 1040/1500
51/51 - 1s - loss: 0.0688 - categorical_accuracy: 0.9731 - val_loss: 2.1994 - val_categorical_accuracy: 0.7826 - 539ms/epoch - 11ms/step
Epoch 1041/1500
51/51 - 1s - loss: 0.0782 - categorical_accuracy: 0.9704 - val_loss: 2.2726 - val_categorical_accuracy: 0.7933 - 573ms/epoch - 11ms/step
Epoch 1042/1500
51/51 - 1s - loss: 0.4645 - categorical_accuracy: 0.8866 - val_loss: 1.6619 - val_categorical_accuracy: 0.7918 - 538ms/epoch - 11ms/step
Epoch 1043/1500
51/51 - 1s - loss: 0.1001 - categorical_accuracy: 0.9629 - val_loss: 1.8273 - val_categorical_accuracy: 0.7950 - 559ms/epoch - 11ms/step
Epoch 1044/1500
51/51 - 1s - loss: 0.0784 - categorical_accuracy: 0.9708 - val_loss: 1.9234 - val_categorical_accuracy: 0.7988 - 589ms/epoch - 12ms/step
Epoch 1045/1500
51/51 - 1s - loss: 0.0695 - categorical_accuracy: 0.9741 - val_loss: 1.9317 - val_categorical_accuracy: 0.7925 - 540ms/epoch - 11ms/step
Epoch 1046/1500
51/51 - 1s - loss: 0.0674 - categorical_accuracy: 0.9752 - val_loss: 1.9582 - val_categorical_accuracy: 0.7966 - 569ms/epoch - 11ms/step
Epoch 1047/1500
51/51 - 1s - loss: 0.0684 - categorical_accuracy: 0.9741 - val_loss: 2.0411 - val_categorical_accuracy: 0.7886 - 523ms/epoch - 10ms/step
Epoch 1048/1500
51/51 - 1s - loss: 0.0667 - categorical_accuracy: 0.9751 - val_loss: 2.0565 - val_categorical_accuracy: 0.7939 - 622ms/epoch - 12ms/step
Epoch 1049/1500
51/51 - 1s - loss: 0.0672 - categorical_accuracy: 0.9751 - val_loss: 2.0227 - val_categorical_accuracy: 0.7926 - 557ms/epoch - 11ms/step
Epoch 1050/1500
51/51 - 1s - loss: 0.0627 - categorical_accuracy: 0.9762 - val_loss: 2.0806 - val_categorical_accuracy: 0.7849 - 598ms/epoch - 12ms/step
Epoch 1051/1500
51/51 - 1s - loss: 0.0639 - categorical_accuracy: 0.9764 - val_loss: 2.0875 - val_categorical_accuracy: 0.7924 - 549ms/epoch - 11ms/step
Epoch 1052/1500
51/51 - 1s - loss: 0.0671 - categorical_accuracy: 0.9741 - val_loss: 2.0909 - val_categorical_accuracy: 0.7878 - 538ms/epoch - 11ms/step
Epoch 1053/1500
51/51 - 1s - loss: 0.0655 - categorical_accuracy: 0.9750 - val_loss: 2.0566 - val_categorical_accuracy: 0.7928 - 597ms/epoch - 12ms/step
Epoch 1054/1500
51/51 - 1s - loss: 0.0647 - categorical_accuracy: 0.9756 - val_loss: 2.1836 - val_categorical_accuracy: 0.7982 - 520ms/epoch - 10ms/step
Epoch 1055/1500
51/51 - 1s - loss: 0.0661 - categorical_accuracy: 0.9750 - val_loss: 2.1070 - val_categorical_accuracy: 0.7929 - 592ms/epoch - 12ms/step
Epoch 1056/1500
51/51 - 1s - loss: 0.0650 - categorical_accuracy: 0.9760 - val_loss: 2.1333 - val_categorical_accuracy: 0.8034 - 560ms/epoch - 11ms/step
Epoch 1057/1500
51/51 - 1s - loss: 0.0647 - categorical_accuracy: 0.9755 - val_loss: 2.1045 - val_categorical_accuracy: 0.7935 - 542ms/epoch - 11ms/step
Epoch 1058/1500
51/51 - 1s - loss: 0.0779 - categorical_accuracy: 0.9687 - val_loss: 2.1277 - val_categorical_accuracy: 0.7910 - 557ms/epoch - 11ms/step
Epoch 1059/1500
51/51 - 1s - loss: 0.0737 - categorical_accuracy: 0.9723 - val_loss: 2.1356 - val_categorical_accuracy: 0.7920 - 558ms/epoch - 11ms/step
Epoch 1060/1500
51/51 - 1s - loss: 0.0789 - categorical_accuracy: 0.9701 - val_loss: 2.1229 - val_categorical_accuracy: 0.7983 - 564ms/epoch - 11ms/step
Epoch 1061/1500
51/51 - 1s - loss: 0.0682 - categorical_accuracy: 0.9742 - val_loss: 2.1459 - val_categorical_accuracy: 0.7989 - 541ms/epoch - 11ms/step
Epoch 1062/1500
51/51 - 1s - loss: 0.0675 - categorical_accuracy: 0.9740 - val_loss: 2.1411 - val_categorical_accuracy: 0.7949 - 598ms/epoch - 12ms/step
Epoch 1063/1500
51/51 - 1s - loss: 0.0640 - categorical_accuracy: 0.9762 - val_loss: 2.1778 - val_categorical_accuracy: 0.7970 - 538ms/epoch - 11ms/step
Epoch 1064/1500
51/51 - 1s - loss: 0.0654 - categorical_accuracy: 0.9745 - val_loss: 2.1695 - val_categorical_accuracy: 0.7892 - 573ms/epoch - 11ms/step
Epoch 1065/1500
51/51 - 1s - loss: 0.0879 - categorical_accuracy: 0.9683 - val_loss: 2.1223 - val_categorical_accuracy: 0.7871 - 548ms/epoch - 11ms/step
Epoch 1066/1500
51/51 - 1s - loss: 0.3906 - categorical_accuracy: 0.9198 - val_loss: 1.1631 - val_categorical_accuracy: 0.7518 - 586ms/epoch - 11ms/step
Epoch 1067/1500
51/51 - 1s - loss: 0.2307 - categorical_accuracy: 0.9187 - val_loss: 1.6098 - val_categorical_accuracy: 0.7947 - 576ms/epoch - 11ms/step
Epoch 1068/1500
51/51 - 1s - loss: 0.0914 - categorical_accuracy: 0.9669 - val_loss: 1.8024 - val_categorical_accuracy: 0.7930 - 527ms/epoch - 10ms/step
Epoch 1069/1500
51/51 - 1s - loss: 0.0726 - categorical_accuracy: 0.9739 - val_loss: 1.8759 - val_categorical_accuracy: 0.7946 - 583ms/epoch - 11ms/step
Epoch 1070/1500
51/51 - 1s - loss: 0.0658 - categorical_accuracy: 0.9749 - val_loss: 1.8751 - val_categorical_accuracy: 0.7959 - 541ms/epoch - 11ms/step
Epoch 1071/1500
51/51 - 1s - loss: 0.0653 - categorical_accuracy: 0.9763 - val_loss: 1.9146 - val_categorical_accuracy: 0.7948 - 562ms/epoch - 11ms/step
Epoch 1072/1500
51/51 - 1s - loss: 0.0662 - categorical_accuracy: 0.9760 - val_loss: 2.0161 - val_categorical_accuracy: 0.7909 - 543ms/epoch - 11ms/step
Epoch 1073/1500
51/51 - 1s - loss: 0.0642 - categorical_accuracy: 0.9755 - val_loss: 1.9839 - val_categorical_accuracy: 0.7927 - 579ms/epoch - 11ms/step
Epoch 1074/1500
51/51 - 1s - loss: 0.0657 - categorical_accuracy: 0.9747 - val_loss: 1.9896 - val_categorical_accuracy: 0.7982 - 557ms/epoch - 11ms/step
Epoch 1075/1500
51/51 - 1s - loss: 0.0669 - categorical_accuracy: 0.9747 - val_loss: 2.0090 - val_categorical_accuracy: 0.7959 - 571ms/epoch - 11ms/step
Epoch 1076/1500
51/51 - 1s - loss: 0.0647 - categorical_accuracy: 0.9753 - val_loss: 2.0300 - val_categorical_accuracy: 0.7970 - 569ms/epoch - 11ms/step
Epoch 1077/1500
51/51 - 1s - loss: 0.0637 - categorical_accuracy: 0.9761 - val_loss: 2.0857 - val_categorical_accuracy: 0.7966 - 521ms/epoch - 10ms/step
Epoch 1078/1500
51/51 - 1s - loss: 0.0617 - categorical_accuracy: 0.9761 - val_loss: 2.1011 - val_categorical_accuracy: 0.7907 - 582ms/epoch - 11ms/step
Epoch 1079/1500
51/51 - 1s - loss: 0.0635 - categorical_accuracy: 0.9751 - val_loss: 2.0798 - val_categorical_accuracy: 0.7853 - 503ms/epoch - 10ms/step
Epoch 1080/1500
51/51 - 1s - loss: 0.0631 - categorical_accuracy: 0.9761 - val_loss: 2.1269 - val_categorical_accuracy: 0.7963 - 572ms/epoch - 11ms/step
Epoch 1081/1500
51/51 - 1s - loss: 0.0609 - categorical_accuracy: 0.9774 - val_loss: 2.1068 - val_categorical_accuracy: 0.7920 - 535ms/epoch - 10ms/step
Epoch 1082/1500
51/51 - 1s - loss: 0.0646 - categorical_accuracy: 0.9760 - val_loss: 2.1394 - val_categorical_accuracy: 0.7949 - 559ms/epoch - 11ms/step
Epoch 1083/1500
51/51 - 1s - loss: 0.0697 - categorical_accuracy: 0.9731 - val_loss: 2.1112 - val_categorical_accuracy: 0.7885 - 605ms/epoch - 12ms/step
Epoch 1084/1500
51/51 - 1s - loss: 0.0677 - categorical_accuracy: 0.9749 - val_loss: 2.1649 - val_categorical_accuracy: 0.7972 - 557ms/epoch - 11ms/step
Epoch 1085/1500
51/51 - 1s - loss: 0.0635 - categorical_accuracy: 0.9753 - val_loss: 2.1663 - val_categorical_accuracy: 0.7984 - 557ms/epoch - 11ms/step
Epoch 1086/1500
51/51 - 1s - loss: 0.0662 - categorical_accuracy: 0.9751 - val_loss: 2.1687 - val_categorical_accuracy: 0.7861 - 549ms/epoch - 11ms/step
Epoch 1087/1500
51/51 - 1s - loss: 0.2462 - categorical_accuracy: 0.9457 - val_loss: 1.5592 - val_categorical_accuracy: 0.7590 - 572ms/epoch - 11ms/step
Epoch 1088/1500
51/51 - 1s - loss: 0.1427 - categorical_accuracy: 0.9474 - val_loss: 1.8470 - val_categorical_accuracy: 0.8007 - 531ms/epoch - 10ms/step
Epoch 1089/1500
51/51 - 1s - loss: 0.0770 - categorical_accuracy: 0.9720 - val_loss: 1.9461 - val_categorical_accuracy: 0.7931 - 588ms/epoch - 12ms/step
Epoch 1090/1500
51/51 - 1s - loss: 0.0713 - categorical_accuracy: 0.9730 - val_loss: 1.9721 - val_categorical_accuracy: 0.7954 - 582ms/epoch - 11ms/step
Epoch 1091/1500
51/51 - 1s - loss: 0.0650 - categorical_accuracy: 0.9747 - val_loss: 2.0292 - val_categorical_accuracy: 0.7898 - 569ms/epoch - 11ms/step
Epoch 1092/1500
51/51 - 1s - loss: 0.0701 - categorical_accuracy: 0.9733 - val_loss: 2.0835 - val_categorical_accuracy: 0.7896 - 578ms/epoch - 11ms/step
Epoch 1093/1500
51/51 - 1s - loss: 0.0722 - categorical_accuracy: 0.9735 - val_loss: 2.0611 - val_categorical_accuracy: 0.7956 - 539ms/epoch - 11ms/step
Epoch 1094/1500
51/51 - 1s - loss: 0.0630 - categorical_accuracy: 0.9755 - val_loss: 2.0896 - val_categorical_accuracy: 0.7945 - 583ms/epoch - 11ms/step
Epoch 1095/1500
51/51 - 1s - loss: 0.0651 - categorical_accuracy: 0.9747 - val_loss: 2.0769 - val_categorical_accuracy: 0.7929 - 544ms/epoch - 11ms/step
Epoch 1096/1500
51/51 - 1s - loss: 0.0612 - categorical_accuracy: 0.9781 - val_loss: 2.1204 - val_categorical_accuracy: 0.7955 - 581ms/epoch - 11ms/step
Epoch 1097/1500
51/51 - 1s - loss: 0.0630 - categorical_accuracy: 0.9759 - val_loss: 2.1302 - val_categorical_accuracy: 0.7964 - 541ms/epoch - 11ms/step
Epoch 1098/1500
51/51 - 1s - loss: 0.0707 - categorical_accuracy: 0.9739 - val_loss: 2.0980 - val_categorical_accuracy: 0.7912 - 544ms/epoch - 11ms/step
Epoch 1099/1500
51/51 - 1s - loss: 0.0663 - categorical_accuracy: 0.9748 - val_loss: 2.1154 - val_categorical_accuracy: 0.7880 - 552ms/epoch - 11ms/step
Epoch 1100/1500
51/51 - 1s - loss: 0.0697 - categorical_accuracy: 0.9731 - val_loss: 2.1051 - val_categorical_accuracy: 0.7921 - 551ms/epoch - 11ms/step
Epoch 1101/1500
51/51 - 1s - loss: 0.0690 - categorical_accuracy: 0.9743 - val_loss: 2.1885 - val_categorical_accuracy: 0.7959 - 596ms/epoch - 12ms/step
Epoch 1102/1500
51/51 - 1s - loss: 0.0648 - categorical_accuracy: 0.9752 - val_loss: 2.2397 - val_categorical_accuracy: 0.7849 - 550ms/epoch - 11ms/step
Epoch 1103/1500
51/51 - 1s - loss: 0.0629 - categorical_accuracy: 0.9758 - val_loss: 2.2105 - val_categorical_accuracy: 0.7945 - 581ms/epoch - 11ms/step
Epoch 1104/1500
51/51 - 1s - loss: 0.0723 - categorical_accuracy: 0.9733 - val_loss: 2.1641 - val_categorical_accuracy: 0.7931 - 548ms/epoch - 11ms/step
Epoch 1105/1500
51/51 - 1s - loss: 0.1248 - categorical_accuracy: 0.9560 - val_loss: 2.0349 - val_categorical_accuracy: 0.7867 - 566ms/epoch - 11ms/step
Epoch 1106/1500
51/51 - 1s - loss: 0.0838 - categorical_accuracy: 0.9689 - val_loss: 2.1542 - val_categorical_accuracy: 0.7876 - 574ms/epoch - 11ms/step
Epoch 1107/1500
51/51 - 1s - loss: 0.2980 - categorical_accuracy: 0.9291 - val_loss: 1.4167 - val_categorical_accuracy: 0.7791 - 567ms/epoch - 11ms/step
Epoch 1108/1500
51/51 - 1s - loss: 0.1242 - categorical_accuracy: 0.9536 - val_loss: 1.8480 - val_categorical_accuracy: 0.7966 - 589ms/epoch - 12ms/step
Epoch 1109/1500
51/51 - 1s - loss: 0.0746 - categorical_accuracy: 0.9719 - val_loss: 1.8844 - val_categorical_accuracy: 0.7970 - 536ms/epoch - 11ms/step
Epoch 1110/1500
51/51 - 1s - loss: 0.0651 - categorical_accuracy: 0.9754 - val_loss: 1.9693 - val_categorical_accuracy: 0.7959 - 584ms/epoch - 11ms/step
Epoch 1111/1500
51/51 - 1s - loss: 0.0626 - categorical_accuracy: 0.9761 - val_loss: 2.0236 - val_categorical_accuracy: 0.7927 - 541ms/epoch - 11ms/step
Epoch 1112/1500
51/51 - 1s - loss: 0.0617 - categorical_accuracy: 0.9769 - val_loss: 2.0681 - val_categorical_accuracy: 0.7955 - 548ms/epoch - 11ms/step
Epoch 1113/1500
51/51 - 1s - loss: 0.0630 - categorical_accuracy: 0.9761 - val_loss: 2.0873 - val_categorical_accuracy: 0.7966 - 537ms/epoch - 11ms/step
Epoch 1114/1500
51/51 - 1s - loss: 0.0616 - categorical_accuracy: 0.9768 - val_loss: 2.1207 - val_categorical_accuracy: 0.7935 - 559ms/epoch - 11ms/step
Epoch 1115/1500
51/51 - 1s - loss: 0.0623 - categorical_accuracy: 0.9770 - val_loss: 2.1283 - val_categorical_accuracy: 0.7987 - 556ms/epoch - 11ms/step
Epoch 1116/1500
51/51 - 1s - loss: 0.0632 - categorical_accuracy: 0.9760 - val_loss: 2.1118 - val_categorical_accuracy: 0.7988 - 539ms/epoch - 11ms/step
Epoch 1117/1500
51/51 - 1s - loss: 0.0617 - categorical_accuracy: 0.9764 - val_loss: 2.1219 - val_categorical_accuracy: 0.8026 - 569ms/epoch - 11ms/step
Epoch 1118/1500
51/51 - 1s - loss: 0.0638 - categorical_accuracy: 0.9757 - val_loss: 2.2058 - val_categorical_accuracy: 0.7961 - 542ms/epoch - 11ms/step
Epoch 1119/1500
51/51 - 1s - loss: 0.0644 - categorical_accuracy: 0.9758 - val_loss: 2.2067 - val_categorical_accuracy: 0.7955 - 594ms/epoch - 12ms/step
Epoch 1120/1500
51/51 - 1s - loss: 0.0701 - categorical_accuracy: 0.9737 - val_loss: 2.1823 - val_categorical_accuracy: 0.7903 - 521ms/epoch - 10ms/step
Epoch 1121/1500
51/51 - 1s - loss: 0.0696 - categorical_accuracy: 0.9733 - val_loss: 2.1505 - val_categorical_accuracy: 0.7837 - 555ms/epoch - 11ms/step
Epoch 1122/1500
51/51 - 1s - loss: 0.0681 - categorical_accuracy: 0.9749 - val_loss: 2.1935 - val_categorical_accuracy: 0.7991 - 542ms/epoch - 11ms/step
Epoch 1123/1500
51/51 - 1s - loss: 0.0675 - categorical_accuracy: 0.9743 - val_loss: 2.1566 - val_categorical_accuracy: 0.7951 - 536ms/epoch - 11ms/step
Epoch 1124/1500
51/51 - 1s - loss: 0.0626 - categorical_accuracy: 0.9761 - val_loss: 2.1103 - val_categorical_accuracy: 0.7900 - 550ms/epoch - 11ms/step
Epoch 1125/1500
51/51 - 1s - loss: 0.0617 - categorical_accuracy: 0.9768 - val_loss: 2.1547 - val_categorical_accuracy: 0.7947 - 534ms/epoch - 10ms/step
Epoch 1126/1500
51/51 - 1s - loss: 0.0632 - categorical_accuracy: 0.9753 - val_loss: 2.1336 - val_categorical_accuracy: 0.7943 - 580ms/epoch - 11ms/step
Epoch 1127/1500
51/51 - 1s - loss: 0.0689 - categorical_accuracy: 0.9738 - val_loss: 2.1938 - val_categorical_accuracy: 0.7916 - 556ms/epoch - 11ms/step
Epoch 1128/1500
51/51 - 1s - loss: 0.0652 - categorical_accuracy: 0.9746 - val_loss: 2.1518 - val_categorical_accuracy: 0.7978 - 570ms/epoch - 11ms/step
Epoch 1129/1500
51/51 - 1s - loss: 0.0686 - categorical_accuracy: 0.9740 - val_loss: 2.1933 - val_categorical_accuracy: 0.7891 - 504ms/epoch - 10ms/step
Epoch 1130/1500
51/51 - 1s - loss: 0.0641 - categorical_accuracy: 0.9769 - val_loss: 2.1797 - val_categorical_accuracy: 0.7835 - 575ms/epoch - 11ms/step
Epoch 1131/1500
51/51 - 1s - loss: 0.0660 - categorical_accuracy: 0.9750 - val_loss: 2.2162 - val_categorical_accuracy: 0.7933 - 549ms/epoch - 11ms/step
Epoch 1132/1500
51/51 - 1s - loss: 0.0625 - categorical_accuracy: 0.9765 - val_loss: 2.2387 - val_categorical_accuracy: 0.7938 - 542ms/epoch - 11ms/step
Epoch 1133/1500
51/51 - 1s - loss: 0.0660 - categorical_accuracy: 0.9747 - val_loss: 2.2888 - val_categorical_accuracy: 0.7967 - 543ms/epoch - 11ms/step
Epoch 1134/1500
51/51 - 1s - loss: 0.0696 - categorical_accuracy: 0.9743 - val_loss: 2.2435 - val_categorical_accuracy: 0.7899 - 557ms/epoch - 11ms/step
Epoch 1135/1500
51/51 - 1s - loss: 0.0776 - categorical_accuracy: 0.9705 - val_loss: 2.3012 - val_categorical_accuracy: 0.7964 - 559ms/epoch - 11ms/step
Epoch 1136/1500
51/51 - 1s - loss: 0.0717 - categorical_accuracy: 0.9733 - val_loss: 2.2294 - val_categorical_accuracy: 0.7847 - 540ms/epoch - 11ms/step
Epoch 1137/1500
51/51 - 1s - loss: 0.0687 - categorical_accuracy: 0.9733 - val_loss: 2.2298 - val_categorical_accuracy: 0.7884 - 618ms/epoch - 12ms/step
Epoch 1138/1500
51/51 - 1s - loss: 0.0731 - categorical_accuracy: 0.9726 - val_loss: 2.2868 - val_categorical_accuracy: 0.7792 - 523ms/epoch - 10ms/step
Epoch 1139/1500
51/51 - 1s - loss: 0.0786 - categorical_accuracy: 0.9710 - val_loss: 2.2514 - val_categorical_accuracy: 0.7894 - 568ms/epoch - 11ms/step
Epoch 1140/1500
51/51 - 1s - loss: 0.0734 - categorical_accuracy: 0.9724 - val_loss: 2.2510 - val_categorical_accuracy: 0.7973 - 518ms/epoch - 10ms/step
Epoch 1141/1500
51/51 - 1s - loss: 0.3906 - categorical_accuracy: 0.9086 - val_loss: 1.5565 - val_categorical_accuracy: 0.7900 - 557ms/epoch - 11ms/step
Epoch 1142/1500
51/51 - 1s - loss: 0.1179 - categorical_accuracy: 0.9560 - val_loss: 1.9012 - val_categorical_accuracy: 0.7961 - 561ms/epoch - 11ms/step
Epoch 1143/1500
51/51 - 1s - loss: 0.0743 - categorical_accuracy: 0.9722 - val_loss: 1.9419 - val_categorical_accuracy: 0.7846 - 536ms/epoch - 11ms/step
Epoch 1144/1500
51/51 - 1s - loss: 0.0646 - categorical_accuracy: 0.9758 - val_loss: 1.9768 - val_categorical_accuracy: 0.7987 - 563ms/epoch - 11ms/step
Epoch 1145/1500
51/51 - 1s - loss: 0.0628 - categorical_accuracy: 0.9769 - val_loss: 2.0677 - val_categorical_accuracy: 0.7921 - 538ms/epoch - 11ms/step
Epoch 1146/1500
51/51 - 1s - loss: 0.0615 - categorical_accuracy: 0.9768 - val_loss: 2.0361 - val_categorical_accuracy: 0.7951 - 571ms/epoch - 11ms/step
Epoch 1147/1500
51/51 - 1s - loss: 0.0799 - categorical_accuracy: 0.9709 - val_loss: 2.0493 - val_categorical_accuracy: 0.7879 - 518ms/epoch - 10ms/step
Epoch 1148/1500
51/51 - 1s - loss: 0.0635 - categorical_accuracy: 0.9753 - val_loss: 2.0790 - val_categorical_accuracy: 0.7893 - 568ms/epoch - 11ms/step
Epoch 1149/1500
51/51 - 1s - loss: 0.0637 - categorical_accuracy: 0.9763 - val_loss: 2.1407 - val_categorical_accuracy: 0.7938 - 524ms/epoch - 10ms/step
Epoch 1150/1500
51/51 - 1s - loss: 0.0694 - categorical_accuracy: 0.9738 - val_loss: 2.1271 - val_categorical_accuracy: 0.7823 - 572ms/epoch - 11ms/step
Epoch 1151/1500
51/51 - 1s - loss: 0.0632 - categorical_accuracy: 0.9770 - val_loss: 2.1103 - val_categorical_accuracy: 0.7960 - 539ms/epoch - 11ms/step
Epoch 1152/1500
51/51 - 1s - loss: 0.0631 - categorical_accuracy: 0.9760 - val_loss: 2.1562 - val_categorical_accuracy: 0.7979 - 557ms/epoch - 11ms/step
Epoch 1153/1500
51/51 - 1s - loss: 0.0604 - categorical_accuracy: 0.9765 - val_loss: 2.1668 - val_categorical_accuracy: 0.7978 - 559ms/epoch - 11ms/step
Epoch 1154/1500
51/51 - 1s - loss: 0.0624 - categorical_accuracy: 0.9766 - val_loss: 2.1805 - val_categorical_accuracy: 0.7968 - 538ms/epoch - 11ms/step
Epoch 1155/1500
51/51 - 1s - loss: 0.0681 - categorical_accuracy: 0.9735 - val_loss: 2.2059 - val_categorical_accuracy: 0.7899 - 585ms/epoch - 11ms/step
Epoch 1156/1500
51/51 - 1s - loss: 0.0620 - categorical_accuracy: 0.9767 - val_loss: 2.1407 - val_categorical_accuracy: 0.7932 - 525ms/epoch - 10ms/step
Epoch 1157/1500
51/51 - 1s - loss: 0.0616 - categorical_accuracy: 0.9764 - val_loss: 2.2232 - val_categorical_accuracy: 0.7921 - 540ms/epoch - 11ms/step
Epoch 1158/1500
51/51 - 1s - loss: 0.0641 - categorical_accuracy: 0.9750 - val_loss: 2.2533 - val_categorical_accuracy: 0.8025 - 537ms/epoch - 11ms/step
Epoch 1159/1500
51/51 - 1s - loss: 0.0599 - categorical_accuracy: 0.9779 - val_loss: 2.2263 - val_categorical_accuracy: 0.7933 - 556ms/epoch - 11ms/step
Epoch 1160/1500
51/51 - 1s - loss: 0.0618 - categorical_accuracy: 0.9767 - val_loss: 2.2186 - val_categorical_accuracy: 0.7906 - 540ms/epoch - 11ms/step
Epoch 1161/1500
51/51 - 1s - loss: 0.0623 - categorical_accuracy: 0.9755 - val_loss: 2.1919 - val_categorical_accuracy: 0.7938 - 557ms/epoch - 11ms/step
Epoch 1162/1500
51/51 - 1s - loss: 0.0589 - categorical_accuracy: 0.9782 - val_loss: 2.2344 - val_categorical_accuracy: 0.8031 - 542ms/epoch - 11ms/step
Epoch 1163/1500
51/51 - 1s - loss: 0.0616 - categorical_accuracy: 0.9767 - val_loss: 2.2766 - val_categorical_accuracy: 0.7903 - 540ms/epoch - 11ms/step
Epoch 1164/1500
51/51 - 1s - loss: 0.0590 - categorical_accuracy: 0.9772 - val_loss: 2.2707 - val_categorical_accuracy: 0.7968 - 557ms/epoch - 11ms/step
Epoch 1165/1500
51/51 - 1s - loss: 0.0597 - categorical_accuracy: 0.9777 - val_loss: 2.2853 - val_categorical_accuracy: 0.7864 - 539ms/epoch - 11ms/step
Epoch 1166/1500
51/51 - 1s - loss: 0.0619 - categorical_accuracy: 0.9764 - val_loss: 2.2847 - val_categorical_accuracy: 0.7976 - 571ms/epoch - 11ms/step
Epoch 1167/1500
51/51 - 1s - loss: 0.7030 - categorical_accuracy: 0.8404 - val_loss: 1.1336 - val_categorical_accuracy: 0.7737 - 527ms/epoch - 10ms/step
Epoch 1168/1500
51/51 - 1s - loss: 0.2258 - categorical_accuracy: 0.9201 - val_loss: 1.5816 - val_categorical_accuracy: 0.7902 - 555ms/epoch - 11ms/step
Epoch 1169/1500
51/51 - 1s - loss: 0.1221 - categorical_accuracy: 0.9555 - val_loss: 1.7473 - val_categorical_accuracy: 0.7892 - 537ms/epoch - 11ms/step
Epoch 1170/1500
51/51 - 1s - loss: 0.0813 - categorical_accuracy: 0.9698 - val_loss: 1.8234 - val_categorical_accuracy: 0.7961 - 566ms/epoch - 11ms/step
Epoch 1171/1500
51/51 - 1s - loss: 0.0692 - categorical_accuracy: 0.9740 - val_loss: 1.9206 - val_categorical_accuracy: 0.7969 - 550ms/epoch - 11ms/step
Epoch 1172/1500
51/51 - 1s - loss: 0.0663 - categorical_accuracy: 0.9758 - val_loss: 1.9864 - val_categorical_accuracy: 0.7976 - 550ms/epoch - 11ms/step
Epoch 1173/1500
51/51 - 1s - loss: 0.0704 - categorical_accuracy: 0.9729 - val_loss: 1.9980 - val_categorical_accuracy: 0.7893 - 571ms/epoch - 11ms/step
Epoch 1174/1500
51/51 - 1s - loss: 0.0695 - categorical_accuracy: 0.9744 - val_loss: 2.0622 - val_categorical_accuracy: 0.7950 - 534ms/epoch - 10ms/step
Epoch 1175/1500
51/51 - 1s - loss: 0.0681 - categorical_accuracy: 0.9748 - val_loss: 2.0183 - val_categorical_accuracy: 0.7986 - 597ms/epoch - 12ms/step
Epoch 1176/1500
51/51 - 1s - loss: 0.0622 - categorical_accuracy: 0.9763 - val_loss: 2.0682 - val_categorical_accuracy: 0.7891 - 527ms/epoch - 10ms/step
Epoch 1177/1500
51/51 - 1s - loss: 0.0613 - categorical_accuracy: 0.9779 - val_loss: 2.0971 - val_categorical_accuracy: 0.7957 - 570ms/epoch - 11ms/step
Epoch 1178/1500
51/51 - 1s - loss: 0.0621 - categorical_accuracy: 0.9758 - val_loss: 2.1211 - val_categorical_accuracy: 0.7956 - 553ms/epoch - 11ms/step
Epoch 1179/1500
51/51 - 1s - loss: 0.0629 - categorical_accuracy: 0.9762 - val_loss: 2.1129 - val_categorical_accuracy: 0.7921 - 541ms/epoch - 11ms/step
Epoch 1180/1500
51/51 - 1s - loss: 0.0633 - categorical_accuracy: 0.9763 - val_loss: 2.1154 - val_categorical_accuracy: 0.7984 - 538ms/epoch - 11ms/step
Epoch 1181/1500
51/51 - 1s - loss: 0.0603 - categorical_accuracy: 0.9776 - val_loss: 2.1426 - val_categorical_accuracy: 0.7989 - 538ms/epoch - 11ms/step
Epoch 1182/1500
51/51 - 1s - loss: 0.0588 - categorical_accuracy: 0.9782 - val_loss: 2.1900 - val_categorical_accuracy: 0.8022 - 572ms/epoch - 11ms/step
Epoch 1183/1500
51/51 - 1s - loss: 0.0601 - categorical_accuracy: 0.9768 - val_loss: 2.1306 - val_categorical_accuracy: 0.7884 - 543ms/epoch - 11ms/step
Epoch 1184/1500
51/51 - 1s - loss: 0.0656 - categorical_accuracy: 0.9761 - val_loss: 2.2164 - val_categorical_accuracy: 0.7850 - 559ms/epoch - 11ms/step
Epoch 1185/1500
51/51 - 1s - loss: 0.0647 - categorical_accuracy: 0.9758 - val_loss: 2.2010 - val_categorical_accuracy: 0.7988 - 512ms/epoch - 10ms/step
Epoch 1186/1500
51/51 - 1s - loss: 0.0631 - categorical_accuracy: 0.9763 - val_loss: 2.1781 - val_categorical_accuracy: 0.7974 - 589ms/epoch - 12ms/step
Epoch 1187/1500
51/51 - 1s - loss: 0.0586 - categorical_accuracy: 0.9776 - val_loss: 2.2791 - val_categorical_accuracy: 0.7966 - 526ms/epoch - 10ms/step
Epoch 1188/1500
51/51 - 1s - loss: 0.0612 - categorical_accuracy: 0.9763 - val_loss: 2.2207 - val_categorical_accuracy: 0.7915 - 571ms/epoch - 11ms/step
Epoch 1189/1500
51/51 - 1s - loss: 0.0563 - categorical_accuracy: 0.9789 - val_loss: 2.2682 - val_categorical_accuracy: 0.7974 - 526ms/epoch - 10ms/step
Epoch 1190/1500
51/51 - 1s - loss: 0.0597 - categorical_accuracy: 0.9770 - val_loss: 2.1859 - val_categorical_accuracy: 0.7969 - 559ms/epoch - 11ms/step
Epoch 1191/1500
51/51 - 1s - loss: 0.0645 - categorical_accuracy: 0.9755 - val_loss: 2.2709 - val_categorical_accuracy: 0.7973 - 581ms/epoch - 11ms/step
Epoch 1192/1500
51/51 - 1s - loss: 0.0641 - categorical_accuracy: 0.9752 - val_loss: 2.3102 - val_categorical_accuracy: 0.7944 - 543ms/epoch - 11ms/step
Epoch 1193/1500
51/51 - 1s - loss: 0.0680 - categorical_accuracy: 0.9747 - val_loss: 2.3420 - val_categorical_accuracy: 0.7845 - 559ms/epoch - 11ms/step
Epoch 1194/1500
51/51 - 1s - loss: 0.0686 - categorical_accuracy: 0.9745 - val_loss: 2.2534 - val_categorical_accuracy: 0.7877 - 542ms/epoch - 11ms/step
Epoch 1195/1500
51/51 - 1s - loss: 0.0704 - categorical_accuracy: 0.9740 - val_loss: 2.2074 - val_categorical_accuracy: 0.7945 - 558ms/epoch - 11ms/step
Epoch 1196/1500
51/51 - 1s - loss: 0.0601 - categorical_accuracy: 0.9775 - val_loss: 2.2441 - val_categorical_accuracy: 0.7922 - 506ms/epoch - 10ms/step
Epoch 1197/1500
51/51 - 1s - loss: 0.0638 - categorical_accuracy: 0.9760 - val_loss: 2.3030 - val_categorical_accuracy: 0.7928 - 581ms/epoch - 11ms/step
Epoch 1198/1500
51/51 - 1s - loss: 0.0659 - categorical_accuracy: 0.9750 - val_loss: 2.2946 - val_categorical_accuracy: 0.7955 - 548ms/epoch - 11ms/step
Epoch 1199/1500
51/51 - 1s - loss: 0.0606 - categorical_accuracy: 0.9769 - val_loss: 2.2402 - val_categorical_accuracy: 0.7924 - 555ms/epoch - 11ms/step
Epoch 1200/1500
51/51 - 1s - loss: 0.0670 - categorical_accuracy: 0.9746 - val_loss: 2.2957 - val_categorical_accuracy: 0.7882 - 546ms/epoch - 11ms/step
Epoch 1201/1500
51/51 - 1s - loss: 0.0623 - categorical_accuracy: 0.9754 - val_loss: 2.2414 - val_categorical_accuracy: 0.7860 - 542ms/epoch - 11ms/step
Epoch 1202/1500
51/51 - 1s - loss: 0.0631 - categorical_accuracy: 0.9754 - val_loss: 2.2693 - val_categorical_accuracy: 0.8001 - 550ms/epoch - 11ms/step
Epoch 1203/1500
51/51 - 1s - loss: 0.0607 - categorical_accuracy: 0.9763 - val_loss: 2.2971 - val_categorical_accuracy: 0.7883 - 524ms/epoch - 10ms/step
Epoch 1204/1500
51/51 - 1s - loss: 0.0646 - categorical_accuracy: 0.9754 - val_loss: 2.3142 - val_categorical_accuracy: 0.7950 - 567ms/epoch - 11ms/step
Epoch 1205/1500
51/51 - 1s - loss: 0.0685 - categorical_accuracy: 0.9750 - val_loss: 2.4137 - val_categorical_accuracy: 0.7789 - 518ms/epoch - 10ms/step
Epoch 1206/1500
51/51 - 1s - loss: 0.3162 - categorical_accuracy: 0.9200 - val_loss: 1.9633 - val_categorical_accuracy: 0.7852 - 554ms/epoch - 11ms/step
Epoch 1207/1500
51/51 - 1s - loss: 0.0939 - categorical_accuracy: 0.9648 - val_loss: 1.9901 - val_categorical_accuracy: 0.7897 - 512ms/epoch - 10ms/step
Epoch 1208/1500
51/51 - 1s - loss: 0.0686 - categorical_accuracy: 0.9742 - val_loss: 2.0789 - val_categorical_accuracy: 0.7955 - 561ms/epoch - 11ms/step
Epoch 1209/1500
51/51 - 1s - loss: 0.0637 - categorical_accuracy: 0.9761 - val_loss: 2.1609 - val_categorical_accuracy: 0.7984 - 572ms/epoch - 11ms/step
Epoch 1210/1500
51/51 - 1s - loss: 0.0635 - categorical_accuracy: 0.9759 - val_loss: 2.1405 - val_categorical_accuracy: 0.7968 - 568ms/epoch - 11ms/step
Epoch 1211/1500
51/51 - 1s - loss: 0.0702 - categorical_accuracy: 0.9732 - val_loss: 2.0942 - val_categorical_accuracy: 0.7926 - 539ms/epoch - 11ms/step
Epoch 1212/1500
51/51 - 1s - loss: 0.0632 - categorical_accuracy: 0.9763 - val_loss: 2.1149 - val_categorical_accuracy: 0.7915 - 520ms/epoch - 10ms/step
Epoch 1213/1500
51/51 - 1s - loss: 0.0602 - categorical_accuracy: 0.9765 - val_loss: 2.1449 - val_categorical_accuracy: 0.7967 - 542ms/epoch - 11ms/step
Epoch 1214/1500
51/51 - 1s - loss: 0.0594 - categorical_accuracy: 0.9778 - val_loss: 2.2369 - val_categorical_accuracy: 0.7870 - 584ms/epoch - 11ms/step
Epoch 1215/1500
51/51 - 1s - loss: 0.0611 - categorical_accuracy: 0.9771 - val_loss: 2.2261 - val_categorical_accuracy: 0.7929 - 590ms/epoch - 12ms/step
Epoch 1216/1500
51/51 - 1s - loss: 0.0609 - categorical_accuracy: 0.9774 - val_loss: 2.2162 - val_categorical_accuracy: 0.7983 - 540ms/epoch - 11ms/step
Epoch 1217/1500
51/51 - 1s - loss: 0.0595 - categorical_accuracy: 0.9771 - val_loss: 2.2012 - val_categorical_accuracy: 0.7926 - 571ms/epoch - 11ms/step
Epoch 1218/1500
51/51 - 1s - loss: 0.0595 - categorical_accuracy: 0.9781 - val_loss: 2.2952 - val_categorical_accuracy: 0.7795 - 575ms/epoch - 11ms/step
Epoch 1219/1500
51/51 - 1s - loss: 0.0608 - categorical_accuracy: 0.9762 - val_loss: 2.2575 - val_categorical_accuracy: 0.7981 - 545ms/epoch - 11ms/step
Epoch 1220/1500
51/51 - 1s - loss: 0.0610 - categorical_accuracy: 0.9770 - val_loss: 2.2272 - val_categorical_accuracy: 0.7969 - 565ms/epoch - 11ms/step
Epoch 1221/1500
51/51 - 1s - loss: 0.0683 - categorical_accuracy: 0.9734 - val_loss: 2.3071 - val_categorical_accuracy: 0.7972 - 545ms/epoch - 11ms/step
Epoch 1222/1500
51/51 - 1s - loss: 0.0689 - categorical_accuracy: 0.9734 - val_loss: 2.2684 - val_categorical_accuracy: 0.7909 - 575ms/epoch - 11ms/step
Epoch 1223/1500
51/51 - 1s - loss: 0.0778 - categorical_accuracy: 0.9714 - val_loss: 2.2953 - val_categorical_accuracy: 0.7545 - 518ms/epoch - 10ms/step
Epoch 1224/1500
51/51 - 1s - loss: 0.1107 - categorical_accuracy: 0.9602 - val_loss: 2.5294 - val_categorical_accuracy: 0.7782 - 550ms/epoch - 11ms/step
Epoch 1225/1500
51/51 - 1s - loss: 0.3330 - categorical_accuracy: 0.9094 - val_loss: 1.9418 - val_categorical_accuracy: 0.7936 - 522ms/epoch - 10ms/step
Epoch 1226/1500
51/51 - 1s - loss: 0.1342 - categorical_accuracy: 0.9519 - val_loss: 1.8908 - val_categorical_accuracy: 0.7972 - 573ms/epoch - 11ms/step
Epoch 1227/1500
51/51 - 1s - loss: 0.0721 - categorical_accuracy: 0.9733 - val_loss: 1.9932 - val_categorical_accuracy: 0.7853 - 536ms/epoch - 11ms/step
Epoch 1228/1500
51/51 - 1s - loss: 0.0668 - categorical_accuracy: 0.9746 - val_loss: 2.0157 - val_categorical_accuracy: 0.7930 - 562ms/epoch - 11ms/step
Epoch 1229/1500
51/51 - 1s - loss: 0.0645 - categorical_accuracy: 0.9753 - val_loss: 2.0678 - val_categorical_accuracy: 0.7946 - 541ms/epoch - 11ms/step
Epoch 1230/1500
51/51 - 1s - loss: 0.0613 - categorical_accuracy: 0.9767 - val_loss: 2.1036 - val_categorical_accuracy: 0.7937 - 521ms/epoch - 10ms/step
Epoch 1231/1500
51/51 - 1s - loss: 0.0582 - categorical_accuracy: 0.9782 - val_loss: 2.1379 - val_categorical_accuracy: 0.7971 - 562ms/epoch - 11ms/step
Epoch 1232/1500
51/51 - 1s - loss: 0.0591 - categorical_accuracy: 0.9779 - val_loss: 2.1407 - val_categorical_accuracy: 0.8001 - 538ms/epoch - 11ms/step
Epoch 1233/1500
51/51 - 1s - loss: 0.0588 - categorical_accuracy: 0.9780 - val_loss: 2.1998 - val_categorical_accuracy: 0.7984 - 550ms/epoch - 11ms/step
Epoch 1234/1500
51/51 - 1s - loss: 0.0603 - categorical_accuracy: 0.9766 - val_loss: 2.1567 - val_categorical_accuracy: 0.7943 - 533ms/epoch - 10ms/step
Epoch 1235/1500
51/51 - 1s - loss: 0.0574 - categorical_accuracy: 0.9782 - val_loss: 2.2162 - val_categorical_accuracy: 0.7971 - 558ms/epoch - 11ms/step
Epoch 1236/1500
51/51 - 1s - loss: 0.0577 - categorical_accuracy: 0.9786 - val_loss: 2.2655 - val_categorical_accuracy: 0.7994 - 520ms/epoch - 10ms/step
Epoch 1237/1500
51/51 - 1s - loss: 0.0593 - categorical_accuracy: 0.9777 - val_loss: 2.1924 - val_categorical_accuracy: 0.7974 - 565ms/epoch - 11ms/step
Epoch 1238/1500
51/51 - 1s - loss: 0.0710 - categorical_accuracy: 0.9738 - val_loss: 2.1889 - val_categorical_accuracy: 0.7889 - 548ms/epoch - 11ms/step
Epoch 1239/1500
51/51 - 1s - loss: 0.0593 - categorical_accuracy: 0.9776 - val_loss: 2.2188 - val_categorical_accuracy: 0.7940 - 548ms/epoch - 11ms/step
Epoch 1240/1500
51/51 - 1s - loss: 0.0571 - categorical_accuracy: 0.9781 - val_loss: 2.2477 - val_categorical_accuracy: 0.7886 - 857ms/epoch - 17ms/step
Epoch 1241/1500
51/51 - 1s - loss: 0.0618 - categorical_accuracy: 0.9765 - val_loss: 2.3127 - val_categorical_accuracy: 0.7990 - 544ms/epoch - 11ms/step
Epoch 1242/1500
51/51 - 1s - loss: 0.0682 - categorical_accuracy: 0.9737 - val_loss: 2.2716 - val_categorical_accuracy: 0.7933 - 584ms/epoch - 11ms/step
Epoch 1243/1500
51/51 - 1s - loss: 0.0591 - categorical_accuracy: 0.9774 - val_loss: 2.2276 - val_categorical_accuracy: 0.7927 - 577ms/epoch - 11ms/step
Epoch 1244/1500
51/51 - 1s - loss: 0.0589 - categorical_accuracy: 0.9779 - val_loss: 2.2855 - val_categorical_accuracy: 0.7898 - 538ms/epoch - 11ms/step
Epoch 1245/1500
51/51 - 1s - loss: 0.0786 - categorical_accuracy: 0.9706 - val_loss: 2.3088 - val_categorical_accuracy: 0.7882 - 610ms/epoch - 12ms/step
Epoch 1246/1500
51/51 - 1s - loss: 0.0706 - categorical_accuracy: 0.9740 - val_loss: 2.2063 - val_categorical_accuracy: 0.7974 - 530ms/epoch - 10ms/step
Epoch 1247/1500
51/51 - 1s - loss: 0.0627 - categorical_accuracy: 0.9760 - val_loss: 2.3848 - val_categorical_accuracy: 0.7970 - 574ms/epoch - 11ms/step
Epoch 1248/1500
51/51 - 1s - loss: 0.2867 - categorical_accuracy: 0.9261 - val_loss: 1.7691 - val_categorical_accuracy: 0.7844 - 559ms/epoch - 11ms/step
Epoch 1249/1500
51/51 - 1s - loss: 0.0984 - categorical_accuracy: 0.9643 - val_loss: 1.9547 - val_categorical_accuracy: 0.7896 - 564ms/epoch - 11ms/step
Epoch 1250/1500
51/51 - 1s - loss: 0.0660 - categorical_accuracy: 0.9763 - val_loss: 2.0811 - val_categorical_accuracy: 0.7970 - 570ms/epoch - 11ms/step
Epoch 1251/1500
51/51 - 1s - loss: 0.0641 - categorical_accuracy: 0.9757 - val_loss: 2.0931 - val_categorical_accuracy: 0.7994 - 557ms/epoch - 11ms/step
Epoch 1252/1500
51/51 - 1s - loss: 0.0624 - categorical_accuracy: 0.9765 - val_loss: 2.1017 - val_categorical_accuracy: 0.7911 - 579ms/epoch - 11ms/step
Epoch 1253/1500
51/51 - 1s - loss: 0.0593 - categorical_accuracy: 0.9777 - val_loss: 2.1177 - val_categorical_accuracy: 0.7916 - 564ms/epoch - 11ms/step
Epoch 1254/1500
51/51 - 1s - loss: 0.0603 - categorical_accuracy: 0.9773 - val_loss: 2.1614 - val_categorical_accuracy: 0.7997 - 596ms/epoch - 12ms/step
Epoch 1255/1500
51/51 - 1s - loss: 0.0627 - categorical_accuracy: 0.9765 - val_loss: 2.1631 - val_categorical_accuracy: 0.7957 - 557ms/epoch - 11ms/step
Epoch 1256/1500
51/51 - 1s - loss: 0.0595 - categorical_accuracy: 0.9772 - val_loss: 2.2235 - val_categorical_accuracy: 0.7940 - 568ms/epoch - 11ms/step
Epoch 1257/1500
51/51 - 1s - loss: 0.0567 - categorical_accuracy: 0.9773 - val_loss: 2.2580 - val_categorical_accuracy: 0.8052 - 552ms/epoch - 11ms/step
Epoch 1258/1500
51/51 - 1s - loss: 0.0584 - categorical_accuracy: 0.9776 - val_loss: 2.2428 - val_categorical_accuracy: 0.7950 - 571ms/epoch - 11ms/step
Epoch 1259/1500
51/51 - 1s - loss: 0.0632 - categorical_accuracy: 0.9752 - val_loss: 2.2658 - val_categorical_accuracy: 0.7933 - 596ms/epoch - 12ms/step
Epoch 1260/1500
51/51 - 1s - loss: 0.0592 - categorical_accuracy: 0.9770 - val_loss: 2.2420 - val_categorical_accuracy: 0.7979 - 538ms/epoch - 11ms/step
Epoch 1261/1500
51/51 - 1s - loss: 0.0625 - categorical_accuracy: 0.9771 - val_loss: 2.2600 - val_categorical_accuracy: 0.7937 - 590ms/epoch - 12ms/step
Epoch 1262/1500
51/51 - 1s - loss: 0.0590 - categorical_accuracy: 0.9769 - val_loss: 2.2789 - val_categorical_accuracy: 0.7916 - 578ms/epoch - 11ms/step
Epoch 1263/1500
51/51 - 1s - loss: 0.0593 - categorical_accuracy: 0.9774 - val_loss: 2.2775 - val_categorical_accuracy: 0.7926 - 583ms/epoch - 11ms/step
Epoch 1264/1500
51/51 - 1s - loss: 0.0597 - categorical_accuracy: 0.9771 - val_loss: 2.2528 - val_categorical_accuracy: 0.7874 - 585ms/epoch - 11ms/step
Epoch 1265/1500
51/51 - 1s - loss: 0.0610 - categorical_accuracy: 0.9763 - val_loss: 2.2905 - val_categorical_accuracy: 0.7937 - 557ms/epoch - 11ms/step
Epoch 1266/1500
51/51 - 1s - loss: 0.0596 - categorical_accuracy: 0.9775 - val_loss: 2.2771 - val_categorical_accuracy: 0.7989 - 596ms/epoch - 12ms/step
Epoch 1267/1500
51/51 - 1s - loss: 0.0680 - categorical_accuracy: 0.9746 - val_loss: 2.2693 - val_categorical_accuracy: 0.7821 - 543ms/epoch - 11ms/step
Epoch 1268/1500
51/51 - 1s - loss: 0.0659 - categorical_accuracy: 0.9745 - val_loss: 2.3010 - val_categorical_accuracy: 0.7868 - 596ms/epoch - 12ms/step
Epoch 1269/1500
51/51 - 1s - loss: 0.0597 - categorical_accuracy: 0.9771 - val_loss: 2.3563 - val_categorical_accuracy: 0.7834 - 563ms/epoch - 11ms/step
Epoch 1270/1500
51/51 - 1s - loss: 0.0602 - categorical_accuracy: 0.9775 - val_loss: 2.3452 - val_categorical_accuracy: 0.7932 - 584ms/epoch - 11ms/step
Epoch 1271/1500
51/51 - 1s - loss: 0.0611 - categorical_accuracy: 0.9765 - val_loss: 2.4028 - val_categorical_accuracy: 0.7979 - 574ms/epoch - 11ms/step
Epoch 1272/1500
51/51 - 1s - loss: 0.0635 - categorical_accuracy: 0.9756 - val_loss: 2.2814 - val_categorical_accuracy: 0.7951 - 536ms/epoch - 11ms/step
Epoch 1273/1500
51/51 - 1s - loss: 0.0641 - categorical_accuracy: 0.9751 - val_loss: 2.3958 - val_categorical_accuracy: 0.7998 - 524ms/epoch - 10ms/step
Epoch 1274/1500
51/51 - 1s - loss: 0.0684 - categorical_accuracy: 0.9742 - val_loss: 2.4451 - val_categorical_accuracy: 0.7818 - 529ms/epoch - 10ms/step
Epoch 1275/1500
51/51 - 1s - loss: 0.0828 - categorical_accuracy: 0.9705 - val_loss: 2.3165 - val_categorical_accuracy: 0.7870 - 548ms/epoch - 11ms/step
Epoch 1276/1500
51/51 - 1s - loss: 0.0619 - categorical_accuracy: 0.9763 - val_loss: 2.2839 - val_categorical_accuracy: 0.7978 - 508ms/epoch - 10ms/step
Epoch 1277/1500
51/51 - 1s - loss: 0.0588 - categorical_accuracy: 0.9780 - val_loss: 2.3240 - val_categorical_accuracy: 0.7969 - 558ms/epoch - 11ms/step
Epoch 1278/1500
51/51 - 1s - loss: 0.0636 - categorical_accuracy: 0.9759 - val_loss: 2.3401 - val_categorical_accuracy: 0.7951 - 508ms/epoch - 10ms/step
Epoch 1279/1500
51/51 - 1s - loss: 0.0643 - categorical_accuracy: 0.9752 - val_loss: 2.3888 - val_categorical_accuracy: 0.7922 - 524ms/epoch - 10ms/step
Epoch 1280/1500
51/51 - 1s - loss: 0.0592 - categorical_accuracy: 0.9769 - val_loss: 2.3620 - val_categorical_accuracy: 0.7875 - 503ms/epoch - 10ms/step
Epoch 1281/1500
51/51 - 1s - loss: 0.0611 - categorical_accuracy: 0.9767 - val_loss: 2.3401 - val_categorical_accuracy: 0.7910 - 570ms/epoch - 11ms/step
Epoch 1282/1500
51/51 - 1s - loss: 0.0586 - categorical_accuracy: 0.9781 - val_loss: 2.3520 - val_categorical_accuracy: 0.7949 - 536ms/epoch - 11ms/step
Epoch 1283/1500
51/51 - 1s - loss: 0.0543 - categorical_accuracy: 0.9793 - val_loss: 2.3694 - val_categorical_accuracy: 0.7910 - 522ms/epoch - 10ms/step
Epoch 1284/1500
51/51 - 1s - loss: 0.0553 - categorical_accuracy: 0.9790 - val_loss: 2.4266 - val_categorical_accuracy: 0.8003 - 705ms/epoch - 14ms/step
Epoch 1285/1500
51/51 - 1s - loss: 0.0594 - categorical_accuracy: 0.9781 - val_loss: 2.3428 - val_categorical_accuracy: 0.7938 - 515ms/epoch - 10ms/step
Epoch 1286/1500
51/51 - 1s - loss: 0.0565 - categorical_accuracy: 0.9787 - val_loss: 2.4048 - val_categorical_accuracy: 0.7958 - 557ms/epoch - 11ms/step
Epoch 1287/1500
51/51 - 1s - loss: 0.0569 - categorical_accuracy: 0.9784 - val_loss: 2.4077 - val_categorical_accuracy: 0.7992 - 505ms/epoch - 10ms/step
Epoch 1288/1500
51/51 - 1s - loss: 0.0571 - categorical_accuracy: 0.9780 - val_loss: 2.4313 - val_categorical_accuracy: 0.7993 - 556ms/epoch - 11ms/step
Epoch 1289/1500
51/51 - 1s - loss: 0.0620 - categorical_accuracy: 0.9765 - val_loss: 2.4035 - val_categorical_accuracy: 0.7845 - 506ms/epoch - 10ms/step
Epoch 1290/1500
51/51 - 1s - loss: 0.0628 - categorical_accuracy: 0.9760 - val_loss: 2.3692 - val_categorical_accuracy: 0.7884 - 526ms/epoch - 10ms/step
Epoch 1291/1500
51/51 - 1s - loss: 0.0603 - categorical_accuracy: 0.9773 - val_loss: 2.3972 - val_categorical_accuracy: 0.7945 - 510ms/epoch - 10ms/step
Epoch 1292/1500
51/51 - 1s - loss: 0.0622 - categorical_accuracy: 0.9758 - val_loss: 2.3956 - val_categorical_accuracy: 0.7925 - 524ms/epoch - 10ms/step
Epoch 1293/1500
51/51 - 1s - loss: 0.0637 - categorical_accuracy: 0.9746 - val_loss: 2.3873 - val_categorical_accuracy: 0.7918 - 520ms/epoch - 10ms/step
Epoch 1294/1500
51/51 - 1s - loss: 0.0603 - categorical_accuracy: 0.9767 - val_loss: 2.4218 - val_categorical_accuracy: 0.7799 - 540ms/epoch - 11ms/step
Epoch 1295/1500
51/51 - 1s - loss: 0.0658 - categorical_accuracy: 0.9749 - val_loss: 2.3722 - val_categorical_accuracy: 0.7945 - 529ms/epoch - 10ms/step
Epoch 1296/1500
51/51 - 1s - loss: 0.0755 - categorical_accuracy: 0.9726 - val_loss: 2.3585 - val_categorical_accuracy: 0.7971 - 522ms/epoch - 10ms/step
Epoch 1297/1500
51/51 - 1s - loss: 0.0752 - categorical_accuracy: 0.9725 - val_loss: 2.3156 - val_categorical_accuracy: 0.7842 - 517ms/epoch - 10ms/step
Epoch 1298/1500
51/51 - 1s - loss: 0.0739 - categorical_accuracy: 0.9720 - val_loss: 2.3846 - val_categorical_accuracy: 0.7866 - 514ms/epoch - 10ms/step
Epoch 1299/1500
51/51 - 1s - loss: 0.0826 - categorical_accuracy: 0.9699 - val_loss: 2.3031 - val_categorical_accuracy: 0.7853 - 593ms/epoch - 12ms/step
Epoch 1300/1500
51/51 - 1s - loss: 0.0635 - categorical_accuracy: 0.9755 - val_loss: 2.4568 - val_categorical_accuracy: 0.7892 - 512ms/epoch - 10ms/step
Epoch 1301/1500
51/51 - 1s - loss: 0.0661 - categorical_accuracy: 0.9749 - val_loss: 2.4169 - val_categorical_accuracy: 0.7955 - 547ms/epoch - 11ms/step
Epoch 1302/1500
51/51 - 0s - loss: 0.0673 - categorical_accuracy: 0.9748 - val_loss: 2.3547 - val_categorical_accuracy: 0.7911 - 499ms/epoch - 10ms/step
Epoch 1303/1500
51/51 - 1s - loss: 0.0615 - categorical_accuracy: 0.9762 - val_loss: 2.4405 - val_categorical_accuracy: 0.7932 - 536ms/epoch - 11ms/step
Epoch 1304/1500
51/51 - 1s - loss: 0.0566 - categorical_accuracy: 0.9789 - val_loss: 2.3665 - val_categorical_accuracy: 0.7966 - 505ms/epoch - 10ms/step
Epoch 1305/1500
51/51 - 1s - loss: 0.2783 - categorical_accuracy: 0.9493 - val_loss: 2.3043 - val_categorical_accuracy: 0.7571 - 549ms/epoch - 11ms/step
Epoch 1306/1500
51/51 - 1s - loss: 0.3501 - categorical_accuracy: 0.8919 - val_loss: 1.7588 - val_categorical_accuracy: 0.7955 - 521ms/epoch - 10ms/step
Epoch 1307/1500
51/51 - 1s - loss: 0.1005 - categorical_accuracy: 0.9623 - val_loss: 1.9329 - val_categorical_accuracy: 0.7927 - 540ms/epoch - 11ms/step
Epoch 1308/1500
51/51 - 0s - loss: 0.0715 - categorical_accuracy: 0.9741 - val_loss: 1.9923 - val_categorical_accuracy: 0.7902 - 491ms/epoch - 10ms/step
Epoch 1309/1500
51/51 - 1s - loss: 0.0626 - categorical_accuracy: 0.9773 - val_loss: 2.0506 - val_categorical_accuracy: 0.7862 - 522ms/epoch - 10ms/step
Epoch 1310/1500
51/51 - 1s - loss: 0.0610 - categorical_accuracy: 0.9767 - val_loss: 2.1413 - val_categorical_accuracy: 0.7901 - 545ms/epoch - 11ms/step
Epoch 1311/1500
51/51 - 1s - loss: 0.0599 - categorical_accuracy: 0.9773 - val_loss: 2.1551 - val_categorical_accuracy: 0.7956 - 530ms/epoch - 10ms/step
Epoch 1312/1500
51/51 - 1s - loss: 0.0572 - categorical_accuracy: 0.9779 - val_loss: 2.2256 - val_categorical_accuracy: 0.7962 - 524ms/epoch - 10ms/step
Epoch 1313/1500
51/51 - 1s - loss: 0.0591 - categorical_accuracy: 0.9779 - val_loss: 2.2165 - val_categorical_accuracy: 0.7916 - 517ms/epoch - 10ms/step
Epoch 1314/1500
51/51 - 1s - loss: 0.0545 - categorical_accuracy: 0.9791 - val_loss: 2.2498 - val_categorical_accuracy: 0.7880 - 540ms/epoch - 11ms/step
Epoch 1315/1500
51/51 - 1s - loss: 0.0588 - categorical_accuracy: 0.9770 - val_loss: 2.2990 - val_categorical_accuracy: 0.8021 - 512ms/epoch - 10ms/step
Epoch 1316/1500
51/51 - 1s - loss: 0.0563 - categorical_accuracy: 0.9792 - val_loss: 2.3127 - val_categorical_accuracy: 0.7946 - 539ms/epoch - 11ms/step
Epoch 1317/1500
51/51 - 1s - loss: 0.0548 - categorical_accuracy: 0.9786 - val_loss: 2.2867 - val_categorical_accuracy: 0.7965 - 514ms/epoch - 10ms/step
Epoch 1318/1500
51/51 - 1s - loss: 0.0583 - categorical_accuracy: 0.9778 - val_loss: 2.3043 - val_categorical_accuracy: 0.7951 - 597ms/epoch - 12ms/step
Epoch 1319/1500
51/51 - 0s - loss: 0.0585 - categorical_accuracy: 0.9780 - val_loss: 2.2869 - val_categorical_accuracy: 0.7982 - 490ms/epoch - 10ms/step
Epoch 1320/1500
51/51 - 1s - loss: 0.0571 - categorical_accuracy: 0.9778 - val_loss: 2.3512 - val_categorical_accuracy: 0.8000 - 548ms/epoch - 11ms/step
Epoch 1321/1500
51/51 - 1s - loss: 0.0594 - categorical_accuracy: 0.9769 - val_loss: 2.3824 - val_categorical_accuracy: 0.7864 - 507ms/epoch - 10ms/step
Epoch 1322/1500
51/51 - 1s - loss: 0.0598 - categorical_accuracy: 0.9772 - val_loss: 2.4240 - val_categorical_accuracy: 0.7919 - 561ms/epoch - 11ms/step
Epoch 1323/1500
51/51 - 1s - loss: 0.0596 - categorical_accuracy: 0.9775 - val_loss: 2.2894 - val_categorical_accuracy: 0.7959 - 585ms/epoch - 11ms/step
Epoch 1324/1500
51/51 - 1s - loss: 0.0590 - categorical_accuracy: 0.9774 - val_loss: 2.3340 - val_categorical_accuracy: 0.7943 - 601ms/epoch - 12ms/step
Epoch 1325/1500
51/51 - 1s - loss: 0.0558 - categorical_accuracy: 0.9783 - val_loss: 2.4036 - val_categorical_accuracy: 0.7994 - 579ms/epoch - 11ms/step
Epoch 1326/1500
51/51 - 1s - loss: 0.0605 - categorical_accuracy: 0.9769 - val_loss: 2.3736 - val_categorical_accuracy: 0.7922 - 560ms/epoch - 11ms/step
Epoch 1327/1500
51/51 - 1s - loss: 0.0654 - categorical_accuracy: 0.9750 - val_loss: 2.3468 - val_categorical_accuracy: 0.7877 - 618ms/epoch - 12ms/step
Epoch 1328/1500
51/51 - 1s - loss: 0.0680 - categorical_accuracy: 0.9745 - val_loss: 2.3173 - val_categorical_accuracy: 0.7824 - 549ms/epoch - 11ms/step
Epoch 1329/1500
51/51 - 1s - loss: 0.5142 - categorical_accuracy: 0.8848 - val_loss: 1.1813 - val_categorical_accuracy: 0.7628 - 582ms/epoch - 11ms/step
Epoch 1330/1500
51/51 - 1s - loss: 0.2323 - categorical_accuracy: 0.9169 - val_loss: 1.7241 - val_categorical_accuracy: 0.7798 - 557ms/epoch - 11ms/step
Epoch 1331/1500
51/51 - 1s - loss: 0.1055 - categorical_accuracy: 0.9610 - val_loss: 1.9940 - val_categorical_accuracy: 0.7761 - 573ms/epoch - 11ms/step
Epoch 1332/1500
51/51 - 1s - loss: 0.0824 - categorical_accuracy: 0.9694 - val_loss: 1.9961 - val_categorical_accuracy: 0.7938 - 575ms/epoch - 11ms/step
Epoch 1333/1500
51/51 - 1s - loss: 0.0672 - categorical_accuracy: 0.9746 - val_loss: 2.0673 - val_categorical_accuracy: 0.7974 - 573ms/epoch - 11ms/step
Epoch 1334/1500
51/51 - 1s - loss: 0.0617 - categorical_accuracy: 0.9772 - val_loss: 2.1308 - val_categorical_accuracy: 0.7984 - 612ms/epoch - 12ms/step
Epoch 1335/1500
51/51 - 1s - loss: 0.0599 - categorical_accuracy: 0.9782 - val_loss: 2.1420 - val_categorical_accuracy: 0.7942 - 549ms/epoch - 11ms/step
Epoch 1336/1500
51/51 - 1s - loss: 0.0616 - categorical_accuracy: 0.9761 - val_loss: 2.1092 - val_categorical_accuracy: 0.7925 - 583ms/epoch - 11ms/step
Epoch 1337/1500
51/51 - 1s - loss: 0.0598 - categorical_accuracy: 0.9775 - val_loss: 2.1464 - val_categorical_accuracy: 0.7912 - 569ms/epoch - 11ms/step
Epoch 1338/1500
51/51 - 1s - loss: 0.0619 - categorical_accuracy: 0.9772 - val_loss: 2.2030 - val_categorical_accuracy: 0.7964 - 566ms/epoch - 11ms/step
Epoch 1339/1500
51/51 - 1s - loss: 0.0562 - categorical_accuracy: 0.9782 - val_loss: 2.2035 - val_categorical_accuracy: 0.7953 - 601ms/epoch - 12ms/step
Epoch 1340/1500
51/51 - 1s - loss: 0.0572 - categorical_accuracy: 0.9783 - val_loss: 2.2235 - val_categorical_accuracy: 0.7949 - 549ms/epoch - 11ms/step
Epoch 1341/1500
51/51 - 1s - loss: 0.0588 - categorical_accuracy: 0.9784 - val_loss: 2.2547 - val_categorical_accuracy: 0.7904 - 550ms/epoch - 11ms/step
Epoch 1342/1500
51/51 - 1s - loss: 0.0587 - categorical_accuracy: 0.9776 - val_loss: 2.2423 - val_categorical_accuracy: 0.7953 - 557ms/epoch - 11ms/step
Epoch 1343/1500
51/51 - 1s - loss: 0.0571 - categorical_accuracy: 0.9780 - val_loss: 2.2914 - val_categorical_accuracy: 0.7975 - 563ms/epoch - 11ms/step
Epoch 1344/1500
51/51 - 1s - loss: 0.0548 - categorical_accuracy: 0.9780 - val_loss: 2.3023 - val_categorical_accuracy: 0.7928 - 582ms/epoch - 11ms/step
Epoch 1345/1500
51/51 - 1s - loss: 0.0569 - categorical_accuracy: 0.9785 - val_loss: 2.3183 - val_categorical_accuracy: 0.7926 - 566ms/epoch - 11ms/step
Epoch 1346/1500
51/51 - 1s - loss: 0.0577 - categorical_accuracy: 0.9782 - val_loss: 2.3147 - val_categorical_accuracy: 0.7903 - 585ms/epoch - 11ms/step
Epoch 1347/1500
51/51 - 1s - loss: 0.0623 - categorical_accuracy: 0.9768 - val_loss: 2.2271 - val_categorical_accuracy: 0.7973 - 534ms/epoch - 10ms/step
Epoch 1348/1500
51/51 - 1s - loss: 0.0564 - categorical_accuracy: 0.9788 - val_loss: 2.3249 - val_categorical_accuracy: 0.8010 - 588ms/epoch - 12ms/step
Epoch 1349/1500
51/51 - 1s - loss: 0.0554 - categorical_accuracy: 0.9789 - val_loss: 2.3539 - val_categorical_accuracy: 0.7891 - 555ms/epoch - 11ms/step
Epoch 1350/1500
51/51 - 1s - loss: 0.0551 - categorical_accuracy: 0.9788 - val_loss: 2.3716 - val_categorical_accuracy: 0.7918 - 586ms/epoch - 11ms/step
Epoch 1351/1500
51/51 - 1s - loss: 0.0584 - categorical_accuracy: 0.9775 - val_loss: 2.3810 - val_categorical_accuracy: 0.7908 - 559ms/epoch - 11ms/step
Epoch 1352/1500
51/51 - 1s - loss: 0.0587 - categorical_accuracy: 0.9786 - val_loss: 2.3526 - val_categorical_accuracy: 0.7908 - 525ms/epoch - 10ms/step
Epoch 1353/1500
51/51 - 1s - loss: 0.0595 - categorical_accuracy: 0.9775 - val_loss: 2.3397 - val_categorical_accuracy: 0.7971 - 611ms/epoch - 12ms/step
Epoch 1354/1500
51/51 - 1s - loss: 0.0600 - categorical_accuracy: 0.9772 - val_loss: 2.3568 - val_categorical_accuracy: 0.7803 - 581ms/epoch - 11ms/step
Epoch 1355/1500
51/51 - 1s - loss: 0.0763 - categorical_accuracy: 0.9730 - val_loss: 2.2683 - val_categorical_accuracy: 0.7937 - 616ms/epoch - 12ms/step
Epoch 1356/1500
51/51 - 1s - loss: 0.0673 - categorical_accuracy: 0.9738 - val_loss: 2.3411 - val_categorical_accuracy: 0.7768 - 590ms/epoch - 12ms/step
Epoch 1357/1500
51/51 - 1s - loss: 0.0738 - categorical_accuracy: 0.9728 - val_loss: 2.3425 - val_categorical_accuracy: 0.7926 - 571ms/epoch - 11ms/step
Epoch 1358/1500
51/51 - 1s - loss: 0.0577 - categorical_accuracy: 0.9773 - val_loss: 2.3029 - val_categorical_accuracy: 0.7902 - 643ms/epoch - 13ms/step
Epoch 1359/1500
51/51 - 1s - loss: 0.0585 - categorical_accuracy: 0.9769 - val_loss: 2.4163 - val_categorical_accuracy: 0.7930 - 568ms/epoch - 11ms/step
Epoch 1360/1500
51/51 - 1s - loss: 0.0616 - categorical_accuracy: 0.9765 - val_loss: 2.3827 - val_categorical_accuracy: 0.7932 - 585ms/epoch - 11ms/step
Epoch 1361/1500
51/51 - 1s - loss: 0.0582 - categorical_accuracy: 0.9776 - val_loss: 2.3726 - val_categorical_accuracy: 0.7954 - 553ms/epoch - 11ms/step
Epoch 1362/1500
51/51 - 1s - loss: 0.0575 - categorical_accuracy: 0.9784 - val_loss: 2.4046 - val_categorical_accuracy: 0.7946 - 573ms/epoch - 11ms/step
Epoch 1363/1500
51/51 - 1s - loss: 0.0599 - categorical_accuracy: 0.9770 - val_loss: 2.3890 - val_categorical_accuracy: 0.7976 - 587ms/epoch - 12ms/step
Epoch 1364/1500
51/51 - 1s - loss: 0.0554 - categorical_accuracy: 0.9793 - val_loss: 2.4639 - val_categorical_accuracy: 0.7957 - 550ms/epoch - 11ms/step
Epoch 1365/1500
51/51 - 1s - loss: 0.0582 - categorical_accuracy: 0.9775 - val_loss: 2.4055 - val_categorical_accuracy: 0.7984 - 568ms/epoch - 11ms/step
Epoch 1366/1500
51/51 - 1s - loss: 0.0606 - categorical_accuracy: 0.9769 - val_loss: 2.4571 - val_categorical_accuracy: 0.7773 - 550ms/epoch - 11ms/step
Epoch 1367/1500
51/51 - 1s - loss: 0.0560 - categorical_accuracy: 0.9782 - val_loss: 2.4541 - val_categorical_accuracy: 0.7964 - 581ms/epoch - 11ms/step
Epoch 1368/1500
51/51 - 1s - loss: 0.0587 - categorical_accuracy: 0.9772 - val_loss: 2.4205 - val_categorical_accuracy: 0.7913 - 504ms/epoch - 10ms/step
Epoch 1369/1500
51/51 - 1s - loss: 0.0547 - categorical_accuracy: 0.9787 - val_loss: 2.4181 - val_categorical_accuracy: 0.7893 - 569ms/epoch - 11ms/step
Epoch 1370/1500
51/51 - 1s - loss: 0.0593 - categorical_accuracy: 0.9779 - val_loss: 2.4559 - val_categorical_accuracy: 0.7945 - 598ms/epoch - 12ms/step
Epoch 1371/1500
51/51 - 1s - loss: 0.0597 - categorical_accuracy: 0.9768 - val_loss: 2.4269 - val_categorical_accuracy: 0.7975 - 569ms/epoch - 11ms/step
Epoch 1372/1500
51/51 - 1s - loss: 0.0596 - categorical_accuracy: 0.9762 - val_loss: 2.4261 - val_categorical_accuracy: 0.7957 - 583ms/epoch - 11ms/step
Epoch 1373/1500
51/51 - 1s - loss: 0.0613 - categorical_accuracy: 0.9765 - val_loss: 2.4853 - val_categorical_accuracy: 0.7921 - 539ms/epoch - 11ms/step
Epoch 1374/1500
51/51 - 1s - loss: 0.0635 - categorical_accuracy: 0.9759 - val_loss: 2.5206 - val_categorical_accuracy: 0.7908 - 668ms/epoch - 13ms/step
Epoch 1375/1500
51/51 - 1s - loss: 0.0655 - categorical_accuracy: 0.9752 - val_loss: 2.4345 - val_categorical_accuracy: 0.7925 - 617ms/epoch - 12ms/step
Epoch 1376/1500
51/51 - 1s - loss: 0.0610 - categorical_accuracy: 0.9772 - val_loss: 2.4295 - val_categorical_accuracy: 0.7800 - 592ms/epoch - 12ms/step
Epoch 1377/1500
51/51 - 1s - loss: 0.0662 - categorical_accuracy: 0.9746 - val_loss: 2.4135 - val_categorical_accuracy: 0.7891 - 569ms/epoch - 11ms/step
Epoch 1378/1500
51/51 - 1s - loss: 0.0598 - categorical_accuracy: 0.9778 - val_loss: 2.4351 - val_categorical_accuracy: 0.7858 - 557ms/epoch - 11ms/step
Epoch 1379/1500
51/51 - 1s - loss: 0.0586 - categorical_accuracy: 0.9773 - val_loss: 2.4421 - val_categorical_accuracy: 0.7923 - 576ms/epoch - 11ms/step
Epoch 1380/1500
51/51 - 1s - loss: 0.0582 - categorical_accuracy: 0.9778 - val_loss: 2.5009 - val_categorical_accuracy: 0.7949 - 537ms/epoch - 11ms/step
Epoch 1381/1500
51/51 - 1s - loss: 0.0603 - categorical_accuracy: 0.9768 - val_loss: 2.5157 - val_categorical_accuracy: 0.7996 - 570ms/epoch - 11ms/step
Epoch 1382/1500
51/51 - 1s - loss: 0.0727 - categorical_accuracy: 0.9721 - val_loss: 2.4409 - val_categorical_accuracy: 0.7959 - 555ms/epoch - 11ms/step
Epoch 1383/1500
51/51 - 1s - loss: 0.0618 - categorical_accuracy: 0.9773 - val_loss: 2.5515 - val_categorical_accuracy: 0.7881 - 555ms/epoch - 11ms/step
Epoch 1384/1500
51/51 - 1s - loss: 0.3943 - categorical_accuracy: 0.9071 - val_loss: 2.0097 - val_categorical_accuracy: 0.7902 - 549ms/epoch - 11ms/step
Epoch 1385/1500
51/51 - 1s - loss: 0.0888 - categorical_accuracy: 0.9673 - val_loss: 2.0653 - val_categorical_accuracy: 0.7802 - 550ms/epoch - 11ms/step
Epoch 1386/1500
51/51 - 1s - loss: 0.0645 - categorical_accuracy: 0.9759 - val_loss: 2.1032 - val_categorical_accuracy: 0.7930 - 582ms/epoch - 11ms/step
Epoch 1387/1500
51/51 - 1s - loss: 0.0574 - categorical_accuracy: 0.9777 - val_loss: 2.1821 - val_categorical_accuracy: 0.7916 - 540ms/epoch - 11ms/step
Epoch 1388/1500
51/51 - 1s - loss: 0.0560 - categorical_accuracy: 0.9791 - val_loss: 2.2706 - val_categorical_accuracy: 0.7962 - 613ms/epoch - 12ms/step
Epoch 1389/1500
51/51 - 1s - loss: 0.0562 - categorical_accuracy: 0.9790 - val_loss: 2.2963 - val_categorical_accuracy: 0.7918 - 550ms/epoch - 11ms/step
Epoch 1390/1500
51/51 - 1s - loss: 0.0583 - categorical_accuracy: 0.9780 - val_loss: 2.2835 - val_categorical_accuracy: 0.7967 - 572ms/epoch - 11ms/step
Epoch 1391/1500
51/51 - 1s - loss: 0.0524 - categorical_accuracy: 0.9800 - val_loss: 2.3538 - val_categorical_accuracy: 0.7966 - 540ms/epoch - 11ms/step
Epoch 1392/1500
51/51 - 1s - loss: 0.0516 - categorical_accuracy: 0.9800 - val_loss: 2.3027 - val_categorical_accuracy: 0.7945 - 577ms/epoch - 11ms/step
Epoch 1393/1500
51/51 - 1s - loss: 0.0526 - categorical_accuracy: 0.9802 - val_loss: 2.3833 - val_categorical_accuracy: 0.7965 - 556ms/epoch - 11ms/step
Epoch 1394/1500
51/51 - 1s - loss: 0.0538 - categorical_accuracy: 0.9794 - val_loss: 2.2908 - val_categorical_accuracy: 0.7995 - 519ms/epoch - 10ms/step
Epoch 1395/1500
51/51 - 1s - loss: 0.0538 - categorical_accuracy: 0.9804 - val_loss: 2.3685 - val_categorical_accuracy: 0.7927 - 540ms/epoch - 11ms/step
Epoch 1396/1500
51/51 - 1s - loss: 0.0589 - categorical_accuracy: 0.9768 - val_loss: 2.3394 - val_categorical_accuracy: 0.7882 - 505ms/epoch - 10ms/step
Epoch 1397/1500
51/51 - 1s - loss: 0.0606 - categorical_accuracy: 0.9772 - val_loss: 2.3533 - val_categorical_accuracy: 0.7938 - 556ms/epoch - 11ms/step
Epoch 1398/1500
51/51 - 1s - loss: 0.0560 - categorical_accuracy: 0.9782 - val_loss: 2.3245 - val_categorical_accuracy: 0.7929 - 525ms/epoch - 10ms/step
Epoch 1399/1500
51/51 - 1s - loss: 0.0568 - categorical_accuracy: 0.9782 - val_loss: 2.3957 - val_categorical_accuracy: 0.7936 - 556ms/epoch - 11ms/step
Epoch 1400/1500
51/51 - 1s - loss: 0.0540 - categorical_accuracy: 0.9796 - val_loss: 2.4242 - val_categorical_accuracy: 0.7968 - 504ms/epoch - 10ms/step
Epoch 1401/1500
51/51 - 1s - loss: 0.0554 - categorical_accuracy: 0.9785 - val_loss: 2.4256 - val_categorical_accuracy: 0.7915 - 521ms/epoch - 10ms/step
Epoch 1402/1500
51/51 - 1s - loss: 0.0566 - categorical_accuracy: 0.9785 - val_loss: 2.4166 - val_categorical_accuracy: 0.7973 - 519ms/epoch - 10ms/step
Epoch 1403/1500
51/51 - 1s - loss: 0.0544 - categorical_accuracy: 0.9792 - val_loss: 2.4561 - val_categorical_accuracy: 0.7850 - 536ms/epoch - 11ms/step
Epoch 1404/1500
51/51 - 1s - loss: 0.0566 - categorical_accuracy: 0.9781 - val_loss: 2.3960 - val_categorical_accuracy: 0.7921 - 519ms/epoch - 10ms/step
Epoch 1405/1500
51/51 - 1s - loss: 0.0592 - categorical_accuracy: 0.9777 - val_loss: 2.3959 - val_categorical_accuracy: 0.7932 - 524ms/epoch - 10ms/step
Epoch 1406/1500
51/51 - 1s - loss: 0.0563 - categorical_accuracy: 0.9783 - val_loss: 2.4512 - val_categorical_accuracy: 0.7911 - 576ms/epoch - 11ms/step
Epoch 1407/1500
51/51 - 1s - loss: 0.0676 - categorical_accuracy: 0.9747 - val_loss: 2.3818 - val_categorical_accuracy: 0.7942 - 519ms/epoch - 10ms/step
Epoch 1408/1500
51/51 - 1s - loss: 0.0558 - categorical_accuracy: 0.9787 - val_loss: 2.4749 - val_categorical_accuracy: 0.7944 - 542ms/epoch - 11ms/step
Epoch 1409/1500
51/51 - 1s - loss: 0.0562 - categorical_accuracy: 0.9774 - val_loss: 2.4028 - val_categorical_accuracy: 0.7938 - 521ms/epoch - 10ms/step
Epoch 1410/1500
51/51 - 1s - loss: 0.0577 - categorical_accuracy: 0.9777 - val_loss: 2.4532 - val_categorical_accuracy: 0.7913 - 565ms/epoch - 11ms/step
Epoch 1411/1500
51/51 - 0s - loss: 0.0615 - categorical_accuracy: 0.9767 - val_loss: 2.4213 - val_categorical_accuracy: 0.7981 - 495ms/epoch - 10ms/step
Epoch 1412/1500
51/51 - 1s - loss: 0.0646 - categorical_accuracy: 0.9760 - val_loss: 2.4150 - val_categorical_accuracy: 0.7948 - 537ms/epoch - 11ms/step
Epoch 1413/1500
51/51 - 1s - loss: 0.0597 - categorical_accuracy: 0.9770 - val_loss: 2.5205 - val_categorical_accuracy: 0.7863 - 505ms/epoch - 10ms/step
Epoch 1414/1500
51/51 - 1s - loss: 0.0782 - categorical_accuracy: 0.9710 - val_loss: 2.4459 - val_categorical_accuracy: 0.7959 - 546ms/epoch - 11ms/step
Epoch 1415/1500
51/51 - 0s - loss: 0.4137 - categorical_accuracy: 0.9110 - val_loss: 1.5490 - val_categorical_accuracy: 0.7761 - 490ms/epoch - 10ms/step
Epoch 1416/1500
51/51 - 1s - loss: 0.1303 - categorical_accuracy: 0.9530 - val_loss: 1.9236 - val_categorical_accuracy: 0.7895 - 523ms/epoch - 10ms/step
Epoch 1417/1500
51/51 - 1s - loss: 0.0693 - categorical_accuracy: 0.9738 - val_loss: 2.0676 - val_categorical_accuracy: 0.7951 - 505ms/epoch - 10ms/step
Epoch 1418/1500
51/51 - 1s - loss: 0.0621 - categorical_accuracy: 0.9758 - val_loss: 2.1191 - val_categorical_accuracy: 0.7903 - 574ms/epoch - 11ms/step
Epoch 1419/1500
51/51 - 1s - loss: 0.0566 - categorical_accuracy: 0.9789 - val_loss: 2.1799 - val_categorical_accuracy: 0.7954 - 542ms/epoch - 11ms/step
Epoch 1420/1500
51/51 - 1s - loss: 0.0551 - categorical_accuracy: 0.9793 - val_loss: 2.2015 - val_categorical_accuracy: 0.7875 - 554ms/epoch - 11ms/step
Epoch 1421/1500
51/51 - 1s - loss: 0.0565 - categorical_accuracy: 0.9787 - val_loss: 2.2556 - val_categorical_accuracy: 0.7880 - 557ms/epoch - 11ms/step
Epoch 1422/1500
51/51 - 1s - loss: 0.0540 - categorical_accuracy: 0.9794 - val_loss: 2.2955 - val_categorical_accuracy: 0.7862 - 554ms/epoch - 11ms/step
Epoch 1423/1500
51/51 - 1s - loss: 0.0517 - categorical_accuracy: 0.9804 - val_loss: 2.2685 - val_categorical_accuracy: 0.7882 - 591ms/epoch - 12ms/step
Epoch 1424/1500
51/51 - 1s - loss: 0.0542 - categorical_accuracy: 0.9794 - val_loss: 2.3208 - val_categorical_accuracy: 0.7930 - 518ms/epoch - 10ms/step
Epoch 1425/1500
51/51 - 1s - loss: 0.0597 - categorical_accuracy: 0.9768 - val_loss: 2.3639 - val_categorical_accuracy: 0.7939 - 604ms/epoch - 12ms/step
Epoch 1426/1500
51/51 - 1s - loss: 0.0554 - categorical_accuracy: 0.9792 - val_loss: 2.3317 - val_categorical_accuracy: 0.7891 - 538ms/epoch - 11ms/step
Epoch 1427/1500
51/51 - 1s - loss: 0.0578 - categorical_accuracy: 0.9789 - val_loss: 2.3568 - val_categorical_accuracy: 0.7857 - 560ms/epoch - 11ms/step
Epoch 1428/1500
51/51 - 1s - loss: 0.0580 - categorical_accuracy: 0.9774 - val_loss: 2.3116 - val_categorical_accuracy: 0.7929 - 580ms/epoch - 11ms/step
Epoch 1429/1500
51/51 - 1s - loss: 0.0537 - categorical_accuracy: 0.9794 - val_loss: 2.3705 - val_categorical_accuracy: 0.7990 - 557ms/epoch - 11ms/step
Epoch 1430/1500
51/51 - 1s - loss: 0.0538 - categorical_accuracy: 0.9789 - val_loss: 2.3706 - val_categorical_accuracy: 0.7882 - 604ms/epoch - 12ms/step
Epoch 1431/1500
51/51 - 1s - loss: 0.0540 - categorical_accuracy: 0.9791 - val_loss: 2.4033 - val_categorical_accuracy: 0.7892 - 540ms/epoch - 11ms/step
Epoch 1432/1500
51/51 - 1s - loss: 0.0571 - categorical_accuracy: 0.9779 - val_loss: 2.3844 - val_categorical_accuracy: 0.7996 - 588ms/epoch - 12ms/step
Epoch 1433/1500
51/51 - 1s - loss: 0.0552 - categorical_accuracy: 0.9787 - val_loss: 2.3337 - val_categorical_accuracy: 0.7943 - 533ms/epoch - 10ms/step
Epoch 1434/1500
51/51 - 1s - loss: 0.0530 - categorical_accuracy: 0.9797 - val_loss: 2.4018 - val_categorical_accuracy: 0.7946 - 567ms/epoch - 11ms/step
Epoch 1435/1500
51/51 - 1s - loss: 0.0564 - categorical_accuracy: 0.9775 - val_loss: 2.3354 - val_categorical_accuracy: 0.7902 - 540ms/epoch - 11ms/step
Epoch 1436/1500
51/51 - 1s - loss: 0.0571 - categorical_accuracy: 0.9789 - val_loss: 2.4200 - val_categorical_accuracy: 0.7918 - 566ms/epoch - 11ms/step
Epoch 1437/1500
51/51 - 1s - loss: 0.0577 - categorical_accuracy: 0.9779 - val_loss: 2.3699 - val_categorical_accuracy: 0.7903 - 560ms/epoch - 11ms/step
Epoch 1438/1500
51/51 - 1s - loss: 0.0623 - categorical_accuracy: 0.9764 - val_loss: 2.4684 - val_categorical_accuracy: 0.7921 - 548ms/epoch - 11ms/step
Epoch 1439/1500
51/51 - 1s - loss: 0.0595 - categorical_accuracy: 0.9777 - val_loss: 2.4950 - val_categorical_accuracy: 0.7665 - 587ms/epoch - 12ms/step
Epoch 1440/1500
51/51 - 1s - loss: 0.0621 - categorical_accuracy: 0.9761 - val_loss: 2.4019 - val_categorical_accuracy: 0.7863 - 541ms/epoch - 11ms/step
Epoch 1441/1500
51/51 - 1s - loss: 0.0532 - categorical_accuracy: 0.9797 - val_loss: 2.4335 - val_categorical_accuracy: 0.7852 - 583ms/epoch - 11ms/step
Epoch 1442/1500
51/51 - 1s - loss: 0.0552 - categorical_accuracy: 0.9785 - val_loss: 2.4195 - val_categorical_accuracy: 0.7955 - 556ms/epoch - 11ms/step
Epoch 1443/1500
51/51 - 1s - loss: 0.0516 - categorical_accuracy: 0.9794 - val_loss: 2.5126 - val_categorical_accuracy: 0.7958 - 584ms/epoch - 11ms/step
Epoch 1444/1500
51/51 - 1s - loss: 0.0645 - categorical_accuracy: 0.9752 - val_loss: 2.4440 - val_categorical_accuracy: 0.7888 - 574ms/epoch - 11ms/step
Epoch 1445/1500
51/51 - 1s - loss: 0.0582 - categorical_accuracy: 0.9779 - val_loss: 2.4347 - val_categorical_accuracy: 0.7920 - 542ms/epoch - 11ms/step
Epoch 1446/1500
51/51 - 1s - loss: 0.0527 - categorical_accuracy: 0.9793 - val_loss: 2.5460 - val_categorical_accuracy: 0.7969 - 586ms/epoch - 11ms/step
Epoch 1447/1500
51/51 - 1s - loss: 0.0511 - categorical_accuracy: 0.9799 - val_loss: 2.4815 - val_categorical_accuracy: 0.7949 - 552ms/epoch - 11ms/step
Epoch 1448/1500
51/51 - 1s - loss: 0.0521 - categorical_accuracy: 0.9797 - val_loss: 2.4829 - val_categorical_accuracy: 0.7925 - 570ms/epoch - 11ms/step
Epoch 1449/1500
51/51 - 1s - loss: 0.0557 - categorical_accuracy: 0.9787 - val_loss: 2.5088 - val_categorical_accuracy: 0.7938 - 534ms/epoch - 10ms/step
Epoch 1450/1500
51/51 - 1s - loss: 0.0604 - categorical_accuracy: 0.9766 - val_loss: 2.4776 - val_categorical_accuracy: 0.7890 - 564ms/epoch - 11ms/step
Epoch 1451/1500
51/51 - 1s - loss: 0.0710 - categorical_accuracy: 0.9736 - val_loss: 2.5235 - val_categorical_accuracy: 0.7957 - 549ms/epoch - 11ms/step
Epoch 1452/1500
51/51 - 1s - loss: 0.0734 - categorical_accuracy: 0.9737 - val_loss: 2.4606 - val_categorical_accuracy: 0.7927 - 563ms/epoch - 11ms/step
Epoch 1453/1500
51/51 - 1s - loss: 0.0592 - categorical_accuracy: 0.9776 - val_loss: 2.4722 - val_categorical_accuracy: 0.7908 - 580ms/epoch - 11ms/step
Epoch 1454/1500
51/51 - 1s - loss: 0.0656 - categorical_accuracy: 0.9746 - val_loss: 2.4391 - val_categorical_accuracy: 0.7806 - 541ms/epoch - 11ms/step
Epoch 1455/1500
51/51 - 1s - loss: 0.0691 - categorical_accuracy: 0.9734 - val_loss: 2.5535 - val_categorical_accuracy: 0.7677 - 608ms/epoch - 12ms/step
Epoch 1456/1500
51/51 - 1s - loss: 0.3658 - categorical_accuracy: 0.9087 - val_loss: 1.9263 - val_categorical_accuracy: 0.7655 - 565ms/epoch - 11ms/step
Epoch 1457/1500
51/51 - 1s - loss: 0.1489 - categorical_accuracy: 0.9464 - val_loss: 1.9842 - val_categorical_accuracy: 0.7916 - 596ms/epoch - 12ms/step
Epoch 1458/1500
51/51 - 1s - loss: 0.0798 - categorical_accuracy: 0.9699 - val_loss: 2.2378 - val_categorical_accuracy: 0.7971 - 595ms/epoch - 12ms/step
Epoch 1459/1500
51/51 - 1s - loss: 0.0675 - categorical_accuracy: 0.9739 - val_loss: 2.1255 - val_categorical_accuracy: 0.7970 - 541ms/epoch - 11ms/step
Epoch 1460/1500
51/51 - 1s - loss: 0.0579 - categorical_accuracy: 0.9783 - val_loss: 2.1738 - val_categorical_accuracy: 0.7898 - 578ms/epoch - 11ms/step
Epoch 1461/1500
51/51 - 1s - loss: 0.0569 - categorical_accuracy: 0.9777 - val_loss: 2.2532 - val_categorical_accuracy: 0.7898 - 520ms/epoch - 10ms/step
Epoch 1462/1500
51/51 - 1s - loss: 0.0560 - categorical_accuracy: 0.9782 - val_loss: 2.3380 - val_categorical_accuracy: 0.7993 - 539ms/epoch - 11ms/step
Epoch 1463/1500
51/51 - 1s - loss: 0.0581 - categorical_accuracy: 0.9781 - val_loss: 2.3171 - val_categorical_accuracy: 0.7921 - 509ms/epoch - 10ms/step
Epoch 1464/1500
51/51 - 1s - loss: 0.0545 - categorical_accuracy: 0.9791 - val_loss: 2.2932 - val_categorical_accuracy: 0.7906 - 550ms/epoch - 11ms/step
Epoch 1465/1500
51/51 - 1s - loss: 0.0506 - categorical_accuracy: 0.9810 - val_loss: 2.4019 - val_categorical_accuracy: 0.7994 - 504ms/epoch - 10ms/step
Epoch 1466/1500
51/51 - 1s - loss: 0.0526 - categorical_accuracy: 0.9793 - val_loss: 2.2622 - val_categorical_accuracy: 0.7949 - 559ms/epoch - 11ms/step
Epoch 1467/1500
51/51 - 1s - loss: 0.0503 - categorical_accuracy: 0.9808 - val_loss: 2.3732 - val_categorical_accuracy: 0.7955 - 518ms/epoch - 10ms/step
Epoch 1468/1500
51/51 - 1s - loss: 0.0520 - categorical_accuracy: 0.9803 - val_loss: 2.4287 - val_categorical_accuracy: 0.7890 - 539ms/epoch - 11ms/step
Epoch 1469/1500
51/51 - 1s - loss: 0.0550 - categorical_accuracy: 0.9793 - val_loss: 2.3439 - val_categorical_accuracy: 0.7902 - 523ms/epoch - 10ms/step
Epoch 1470/1500
51/51 - 1s - loss: 0.0541 - categorical_accuracy: 0.9794 - val_loss: 2.3532 - val_categorical_accuracy: 0.7898 - 538ms/epoch - 11ms/step
Epoch 1471/1500
51/51 - 1s - loss: 0.0498 - categorical_accuracy: 0.9803 - val_loss: 2.4553 - val_categorical_accuracy: 0.7998 - 544ms/epoch - 11ms/step
Epoch 1472/1500
51/51 - 1s - loss: 0.0568 - categorical_accuracy: 0.9787 - val_loss: 2.4227 - val_categorical_accuracy: 0.7836 - 513ms/epoch - 10ms/step
Epoch 1473/1500
51/51 - 1s - loss: 0.0561 - categorical_accuracy: 0.9787 - val_loss: 2.4389 - val_categorical_accuracy: 0.7938 - 552ms/epoch - 11ms/step
Epoch 1474/1500
51/51 - 1s - loss: 0.0523 - categorical_accuracy: 0.9797 - val_loss: 2.4369 - val_categorical_accuracy: 0.7857 - 528ms/epoch - 10ms/step
Epoch 1475/1500
51/51 - 1s - loss: 0.0556 - categorical_accuracy: 0.9780 - val_loss: 2.4535 - val_categorical_accuracy: 0.7929 - 543ms/epoch - 11ms/step
Epoch 1476/1500
51/51 - 0s - loss: 0.0530 - categorical_accuracy: 0.9801 - val_loss: 2.4259 - val_categorical_accuracy: 0.7829 - 497ms/epoch - 10ms/step
Epoch 1477/1500
51/51 - 1s - loss: 0.0528 - categorical_accuracy: 0.9798 - val_loss: 2.4757 - val_categorical_accuracy: 0.7947 - 549ms/epoch - 11ms/step
Epoch 1478/1500
51/51 - 1s - loss: 0.0524 - categorical_accuracy: 0.9799 - val_loss: 2.5000 - val_categorical_accuracy: 0.7971 - 524ms/epoch - 10ms/step
Epoch 1479/1500
51/51 - 1s - loss: 0.0579 - categorical_accuracy: 0.9779 - val_loss: 2.5048 - val_categorical_accuracy: 0.7929 - 566ms/epoch - 11ms/step
Epoch 1480/1500
51/51 - 1s - loss: 0.0587 - categorical_accuracy: 0.9775 - val_loss: 2.4011 - val_categorical_accuracy: 0.7950 - 515ms/epoch - 10ms/step
Epoch 1481/1500
51/51 - 1s - loss: 0.0548 - categorical_accuracy: 0.9785 - val_loss: 2.4536 - val_categorical_accuracy: 0.7957 - 520ms/epoch - 10ms/step
Epoch 1482/1500
51/51 - 1s - loss: 0.0543 - categorical_accuracy: 0.9791 - val_loss: 2.5674 - val_categorical_accuracy: 0.7949 - 520ms/epoch - 10ms/step
Epoch 1483/1500
51/51 - 1s - loss: 0.0523 - categorical_accuracy: 0.9798 - val_loss: 2.5345 - val_categorical_accuracy: 0.7890 - 535ms/epoch - 10ms/step
Epoch 1484/1500
51/51 - 1s - loss: 0.0530 - categorical_accuracy: 0.9793 - val_loss: 2.4588 - val_categorical_accuracy: 0.7896 - 520ms/epoch - 10ms/step
Epoch 1485/1500
51/51 - 1s - loss: 0.0575 - categorical_accuracy: 0.9781 - val_loss: 2.5025 - val_categorical_accuracy: 0.7965 - 552ms/epoch - 11ms/step
Epoch 1486/1500
51/51 - 1s - loss: 0.0572 - categorical_accuracy: 0.9786 - val_loss: 2.5567 - val_categorical_accuracy: 0.7831 - 552ms/epoch - 11ms/step
Epoch 1487/1500
51/51 - 1s - loss: 0.3182 - categorical_accuracy: 0.9196 - val_loss: 2.0835 - val_categorical_accuracy: 0.7950 - 507ms/epoch - 10ms/step
Epoch 1488/1500
51/51 - 1s - loss: 0.0774 - categorical_accuracy: 0.9704 - val_loss: 2.1850 - val_categorical_accuracy: 0.7905 - 532ms/epoch - 10ms/step
Epoch 1489/1500
51/51 - 0s - loss: 0.0593 - categorical_accuracy: 0.9778 - val_loss: 2.2401 - val_categorical_accuracy: 0.7935 - 500ms/epoch - 10ms/step
Epoch 1490/1500
51/51 - 1s - loss: 0.0538 - categorical_accuracy: 0.9794 - val_loss: 2.3335 - val_categorical_accuracy: 0.7978 - 529ms/epoch - 10ms/step
Epoch 1491/1500
51/51 - 1s - loss: 0.0516 - categorical_accuracy: 0.9804 - val_loss: 2.3293 - val_categorical_accuracy: 0.7935 - 501ms/epoch - 10ms/step
Epoch 1492/1500
51/51 - 1s - loss: 0.0510 - categorical_accuracy: 0.9804 - val_loss: 2.3525 - val_categorical_accuracy: 0.7969 - 549ms/epoch - 11ms/step
Epoch 1493/1500
51/51 - 0s - loss: 0.0609 - categorical_accuracy: 0.9772 - val_loss: 2.3403 - val_categorical_accuracy: 0.7904 - 491ms/epoch - 10ms/step
Epoch 1494/1500
51/51 - 1s - loss: 0.0534 - categorical_accuracy: 0.9794 - val_loss: 2.4046 - val_categorical_accuracy: 0.7928 - 540ms/epoch - 11ms/step
Epoch 1495/1500
51/51 - 1s - loss: 0.0539 - categorical_accuracy: 0.9799 - val_loss: 2.4001 - val_categorical_accuracy: 0.7890 - 503ms/epoch - 10ms/step
Epoch 1496/1500
51/51 - 1s - loss: 0.0516 - categorical_accuracy: 0.9801 - val_loss: 2.4578 - val_categorical_accuracy: 0.7918 - 540ms/epoch - 11ms/step
Epoch 1497/1500
51/51 - 0s - loss: 0.0491 - categorical_accuracy: 0.9806 - val_loss: 2.4459 - val_categorical_accuracy: 0.7965 - 500ms/epoch - 10ms/step
Epoch 1498/1500
51/51 - 1s - loss: 0.0525 - categorical_accuracy: 0.9802 - val_loss: 2.4051 - val_categorical_accuracy: 0.7925 - 580ms/epoch - 11ms/step
Epoch 1499/1500
51/51 - 1s - loss: 0.0508 - categorical_accuracy: 0.9804 - val_loss: 2.5100 - val_categorical_accuracy: 0.7813 - 524ms/epoch - 10ms/step
Epoch 1500/1500
51/51 - 1s - loss: 0.0566 - categorical_accuracy: 0.9788 - val_loss: 2.4195 - val_categorical_accuracy: 0.7926 - 534ms/epoch - 10ms/step

#reticulate::py_last_error()

#We can then compute the average of the per-epoch ACC scores for all folds:

average_acc_history <- data.frame(
  epoch = seq(1:ncol(all_acc_histories)),
  validation_acc = apply(all_acc_histories, 2, mean)
)


max(average_acc_history$validation_acc)

[1] 0.8075095

library(ggplot2)
ggplot(average_acc_history, aes(x = epoch, y = validation_acc)) + geom_line()

#It may be a bit hard to see the plot due to scaling issues and relatively high variance. Let's use `geom_smooth()` to try to get a clearer picture:
ggplot(average_acc_history, aes(x = epoch, y = validation_acc)) + geom_smooth()

# Evaluate on Testset
eval <- evaluate(model, test_data, test_targets, verbose = 1)

  1/423 [..............................] - ETA: 11s - loss: 1.9922 - categorical_accuracy: 0.8125
 12/423 [..............................] - ETA: 1s - loss: 3.1516 - categorical_accuracy: 0.7630 
 21/423 [>.............................] - ETA: 2s - loss: 3.5001 - categorical_accuracy: 0.7366
 50/423 [==>...........................] - ETA: 1s - loss: 3.1132 - categorical_accuracy: 0.7437
 78/423 [====>.........................] - ETA: 0s - loss: 3.0984 - categorical_accuracy: 0.7456
106/423 [======>.......................] - ETA: 0s - loss: 3.1120 - categorical_accuracy: 0.7403
135/423 [========>.....................] - ETA: 0s - loss: 3.1898 - categorical_accuracy: 0.7398
165/423 [==========>...................] - ETA: 0s - loss: 3.1666 - categorical_accuracy: 0.7403
195/423 [============>.................] - ETA: 0s - loss: 3.1034 - categorical_accuracy: 0.7439
225/423 [==============>...............] - ETA: 0s - loss: 3.1261 - categorical_accuracy: 0.7408
254/423 [=================>............] - ETA: 0s - loss: 3.1729 - categorical_accuracy: 0.7384
282/423 [===================>..........] - ETA: 0s - loss: 3.1861 - categorical_accuracy: 0.7390
310/423 [====================>.........] - ETA: 0s - loss: 3.1721 - categorical_accuracy: 0.7380
340/423 [=======================>......] - ETA: 0s - loss: 3.1759 - categorical_accuracy: 0.7375
369/423 [=========================>....] - ETA: 0s - loss: 3.1804 - categorical_accuracy: 0.7382
397/423 [===========================>..] - ETA: 0s - loss: 3.1878 - categorical_accuracy: 0.7387
422/423 [============================>.] - ETA: 0s - loss: 3.1932 - categorical_accuracy: 0.7379
423/423 [==============================] - 1s 2ms/step - loss: 3.1921 - categorical_accuracy: 0.7380

423/423 [==============================] - 1s 2ms/step - loss: 3.1921 - categorical_accuracy: 0.7380

eval

                loss categorical_accuracy 
           3.1921480            0.7380019 

# Save model and history, please change the name
# write.csv(average_acc_history, "../Doc/Versuch 5/Try 5.csv", row.names=FALSE)
# save_model_hdf5(model, "../Doc/Versuch 5/model 5.hfd5", overwrite = TRUE, include_optimizer = TRUE)

# Load model
# Use model_history as precaution
# model_history <- load_model_hdf5("../Doc/Versuch 5/model 5.hfd5", custom_objects = NULL, compile = TRUE)